Video Processing Research Papers - Academia.edu (original) (raw)

Purpose-The purpose of this paper is to find a real-time parking location for a four-wheeler. Design/methodology/approach-Real-time parking availability using specific infrastructure requires a high cost of installation and maintenance... more

Purpose-The purpose of this paper is to find a real-time parking location for a four-wheeler. Design/methodology/approach-Real-time parking availability using specific infrastructure requires a high cost of installation and maintenance cost, which is not affordable to all urban cities. The authors present statistical block matching algorithm (SBMA) for real-time parking management in small-town cities such as Bhavnagar using an in-built surveillance CCTV system, which is not installed for parking application. In particular, data from a camera situated in a mall was used to detect the parking status of some specific parking places using a region of interest (ROI). The method proposed computes the mean value of the pixels inside the ROI using blocks of different sizes (8 Â 10 and 20 Â 35), and the values were compared among different frames. When the difference between frames is more significant than a threshold, the process generates "no parking space for that place." Otherwise, the method yields "parking place available." Then, this information is used to print a bounding box on the parking places with the color green/red to show the availability of the parking place. Findings-The real-time feedback loop (car parking positions) helps the presented model and dynamically refines the parking strategy and parking position to the users. A whole-day experiment/validation is shown in this paper, where the evaluation of the method is performed using pattern recognition metrics for classification: precision, recall and F1 score. Originality/value-The authors found real-time parking availability for Himalaya Mall situated in Bhavnagar, Gujarat, for 18th June 2018 video using the SBMA method with accountable computational time for finding parking slots. The limitations of the presented method with future implementation are discussed at the end of this paper.

In this paper we propose a new complex method for automatic football video summarization, the method we have provided here does the summarizing by tow other methods, one of them do that by detecting the events and other one do that... more

In this paper we propose a new complex method for automatic football video summarization, the method we have provided here does the summarizing by tow other methods, one of them do that by detecting the events and other one do that without detecting the events. One of the tools the second method used to do this was distinguishing between the views of the goal and the field-center and the first method used the slow motion features. Experimental results show the Complex method is more accurate than each of the used methods.

For many audiovisual applications, the integration and synchronization of audio and video signals is essential. The objective of this paper is to develop a system that displays the active objects in the captured video signal, integrated... more

For many audiovisual applications, the integration and synchronization of audio and video signals is essential. The objective of this paper is to develop a system that displays the active objects in the captured video signal, integrated with their respective audio signals in the form of text. The video and audio signals are captured and processed separately. The signals are buffered and integrated and synchronized using a time-stamping technique. Time-stamps provide the timing information for each of the audio and video processes, the speech recognition and the object detection, respectively. This information is necessary to correlate the audio packets to the video frames. Hence, integration is achieved without the use of video information, such as lip movements. The results obtained are based on a specific implementation of the speech recognition module, which is determined to be the bottleneck process in the proposed system.

Rainy image restoration is considered as one of the most important image restorations aspects to improve the outdoor vision. Many fields have used this kind of restorations such as driving assistant, environment monitoring, animals... more

Rainy image restoration is considered as one of the most important image restorations aspects to improve the outdoor vision. Many fields have used this kind of restorations such as driving assistant, environment monitoring, animals monitoring, computer vision, face recognition, object recognition and personal photos. Image restoration simply means how to remove the noise from the images. Most of the images have some noises from the environment. Moreover, image quality assessment plays an important role in the valuation of image enhancement algorithms. In this research, we will use a total variation to remove rain streaks from a single image. It shows a good performance compared to other methods, using some measurements MSE, PSNR, and VIF for an image with references and BRISQUE for an image without references.

Video event detection (VED) is a challenging task especially with a large variety of objects in the environment. Even though there exist numerous algorithms for event detection, most of them are unsuitable for a typical consumer purpose.... more

Video event detection (VED) is a challenging task especially with a large variety of objects in the environment. Even though there exist numerous algorithms for event detection, most of them are unsuitable for a typical consumer purpose. A hybrid method for detecting and identifying the moving objects by their color and spatial information is presented in this paper. In tracking multiple moving objects, the system makes use of motion of changed regions. In this approach, first, the object detector will look for the existence of objects that have already been registered. Then the control is passed on to an event detector which will wait for an event to happen which can be object placement or object removal. The object detector becomes active only if any event is detected. Simple training procedure using a single color camera in HSV color space makes it a consumer application. The proposed model has proved to be robust in various indoor environments and different types of background scenes. The experimental results prove the feasibility of the proposed method.

Recent advancements in activity recognition from sports videos have attracted wide scientific interest of the Computer Vision community. However, the activity recognition problem from cricket video sequences is largely under-represented... more

Recent advancements in activity recognition from sports videos have attracted wide scientific interest of the Computer Vision community. However, the activity recognition problem from cricket video sequences is largely under-represented in the literature. This paper aims to devise a convolutional neural network (CNN) based model for sports activity recognition. The model is trained on the pre-trained VGG16, VGG19, ResNet50, and Inception V3 Models and tested on the clustered cricket videos frames extracted from the data set especially prepared for this research. The clustering of the frames is done by using K-Mean clustering algorithm. K-Fold cross validation is done which gave an accuracy of 99% on clustered data and 91% on un-clustered data. The accuracy and time complexity of the proposed method is better as compared to the state of the art methods used for activity recognition from videos.

Balancing computational efficiency with recognition accuracy is one of the major challenges in real-world video-based face recognition. A significant design decision for any such system is whether to process and use all possible faces... more

Balancing computational efficiency with recognition accuracy is one of the major challenges in real-world video-based face recognition. A significant design decision for any such system is whether to process and use all possible faces detected over the video frames, or whether to select only a few 'best' faces. This paper presents a video face recognition system based on probabilistic Multi-Region Histograms to characterise performance trade-offs in: (i) selecting a subset of faces compared to using all faces, and (ii) combining information from all faces via clustering. Three face selection metrics are evaluated for choosing a subset: face detection confidence, random subset, and sequential selection. Experiments on the recently introduced MOBIO dataset indicate that the usage of all faces through clustering always outperformed selecting only a subset of faces. The experiments also show that the face selection metric based on face detection confidence generally provides better recognition performance than random or sequential sampling. Moreover, the optimal number of faces varies drastically across selection metric and subsets of MOBIO. Given the trade-offs between computational effort, recognition accuracy and robustness, it is recommended that face feature clustering would be most advantageous in batch processing (particularly for video-based watchlists), whereas face selection methods should be limited to applications with significant computational restrictions.

The ultimate Aim of ASIC verification is to obtain the highest possible level of confidence in the correctness of a design, attempt to find design errors and show that the design implements the specification. Complexity of ASIC is growing... more

The ultimate Aim of ASIC verification is to obtain the highest possible level of confidence in the correctness of a design, attempt to find design errors and show that the design implements the specification. Complexity of ASIC is growing exponentially and the market is pressuring design cycle times to decrease. Traditional methods of verification have proven to be insufficient for Digital Image processing applications. We develop a new verification method based on SystemVerilog verification with MATLAB to accelerate verification. The co-simulation is accomplished using MATLAB and SystemVerilog coupled through the DPI. Here is used the Image Resize design verification as case study by using co-simulation method between SystemVerilog and MATLAB. Golden reference will be made using MATLAB In-built functions, while rest of the Verification Environment are in SystemVerilog. The goal is to find more bugs from the Design as compared to traditional method of Verification, reduce time to ve...

Noise can significantly impact the effectiveness of video processing algorithms. This paper proposes a fast white-noise variance estimation that is reliable even in images with large textured areas. This method finds intensity-homogeneous... more

Noise can significantly impact the effectiveness of video processing algorithms. This paper proposes a fast white-noise variance estimation that is reliable even in images with large textured areas. This method finds intensity-homogeneous blocks first and then estimates the noise variance in these blocks, taking image structure into account. This paper proposes a new measure to determine homogeneous blocks and a new structure analyzer for rejecting blocks with structure. This analyzer is based on high-pass operators and special masks for corners to stabilize the homogeneity estimation. For typical video quality (PSNR of 20-40 dB), the proposed method outperforms other methods significantly and the worst-case estimation error is 3 dB, which is suitable for real applications such as video broadcasts. The method performs well both in highly noisy and good-quality images. It also works well in images including few uniform blocks.

Object tracking in video sequences is an important task in many applications such as video surveillance, traffic monitoring, marketing and sport analysis. In order to enhance these technologies, an objective performance evaluation is... more

Object tracking in video sequences is an important task in many applications such as video surveillance, traffic monitoring, marketing and sport analysis. In order to enhance these technologies, an objective performance evaluation is needed. This evaluation requires to test the system with a given dataset and compare the output with the ground truth. One of the contributions of the TRICTRAC project is the supply to the video processing community of synthetic, high-definition video content of Pan-Tilt-Zoom (PTZ) cameras with 3D ground truth including the parameters of the cameras and the mobile objects. This paper presents this novel dataset.

The demand for credit is increasing constantly. Banks are looking for various methods of credit evaluation that provide the most accurate results in a shorter period in order to minimize their rising risks. This study focuses on various... more

The demand for credit is increasing constantly. Banks are looking for various methods of credit evaluation that provide the most accurate results in a shorter period in order to minimize their rising risks. This study focuses on various methods that enable the banks to increase their asset quality without market loss regarding the credit allocation process. These methods enable the automatic evaluation of loan applications in line with the sector practices, and enable determination of credit policies/strategies based on actual needs. Within the scope of this study, the relationship between the predetermined attributes and the credit limit outputs are analyzed by using a sample data set of consumer loans. Random forest (RF), sequential minimal optimization (SMO), PART, decision table (DT), J48, multilayer perceptron (MP), JRip, naïve Bayes (NB), one rule (OneR) and zero rule (ZeroR) algorithms were used in this process. As a result of this analysis, SMO, PART and random forest algorithms are the top three approaches for determining customer credit limits.

We present the Convergence Processor, an innovative component that integrates a high performance 32- bit RISC core, a custom IP core optimised for header-processing and other blocks for specific communication interfaces required for the... more

We present the Convergence Processor, an innovative component that integrates a high performance 32- bit RISC core, a custom IP core optimised for header-processing and other blocks for specific communication interfaces required for the delivery of broadband residential applications. The component is a System-on-Chip supporting the real time processing of packets and protocol data units from various networking interfaces. Its

Coronavirus disease (COVID-19) altered the way of caregiving and the new pandemic forced the health systems to adopt new treatment protocols in which remote follow-up is essential. This paper introduces a proposed system to link a remote... more

Coronavirus disease (COVID-19) altered the way of caregiving and the new pandemic forced the health systems to adopt new treatment protocols in which remote follow-up is essential. This paper introduces a proposed system to link a remote healthcare unit as it is inside the hospital. Two different network protocols; a global system for mobile communication (GSM) and Wi-Fi were used to simulate the heath data transfer from the two different geographical locations, using Raspberry Pi development board and Microcontroller units. Message queuing telemetry transport (MQTT) protocol was employed to transfer the measured data from the healthcare unit to the hospital's Gateway. The gateway is used to route the aggregated health data from healthcare units to the hospital server, doctors' dashboards, and the further processing. The system was successfully implemented and tested, where the experimental tests show that the remote healthcare units using a GSM network consumed about 900 mWh. A high percentage of success data packets transfer was recorded within the network framework as it reaches 99.89% with an average round trip time (RTT) of 7.5 milliseconds and a data transfer rate up to 12.3 kbps.

The multitude of video formats in television and multimedia systems requires extensive use of video scaling. For this purpose, we present a new topology for flexible sample-rate conversion with polyphase FIR filters. Earlier limitations... more

The multitude of video formats in television and multimedia systems requires extensive use of video scaling. For this purpose, we present a new topology for flexible sample-rate conversion with polyphase FIR filters. Earlier limitations that existed with direct form and transposed topologies, have been removed. For any desired number of filter taps a topology can be given, featuring panoramic (or other) distortions that cross the 1:1 ratio (up-down and vice versa) without stalling the data stream. Scaling quality is maintained by using the step-response technique, which avoids DC-ripple caused by quantization in the polyphase filter coefficients. A major advantage of our FIR-filter approach is that it is not limited to video processing and can be applied in those cases where flexible sample-rate conversion or one scaler implementation for all ratios is needed (e.g. audio, graphics).

In this paper, we derive a principal component regression (PCR) method for estimating the optical flow between frames of video sequences according to a pel-recursive manner. This is an easy alternative to dealing with mixtures of motion... more

In this paper, we derive a principal component regression (PCR) method for estimating the optical flow between frames of video sequences according to a pel-recursive manner. This is an easy alternative to dealing with mixtures of motion vectors due to the lack of too much prior information on their statistics (although they are supposed to be normal). The 2D motion vector estimation takes into consideration local image properties. The main advantage of the developed procedure is that no knowledge of the noise distribution is necessary. Preliminary experiments indicate that this approach provides robust estimates of the optical flow. KEY WORDS Motion estimation, principal component regression, and surveillance. 1.

Dynamically changing background ("dynamic background") still presents a great challenge to many motion-based video surveillance systems. In the context of event detection, it is a major source of false alarms. There is a strong need from... more

Dynamically changing background ("dynamic background") still presents a great challenge to many motion-based video surveillance systems. In the context of event detection, it is a major source of false alarms. There is a strong need from the security industry either to detect and suppress these false alarms, or dampen the effects of background changes, so as to increase the sensitivity to meaningful events of interest. In this paper, we restrict our focus to one of the most common causes of dynamic background changes: that of swaying tree branches and their shadows under windy conditions. Considering the ultimate goal in a video analytics pipeline, we formulate a new dynamic background detection problem as a signal processing alternative to the previously described but unreliable computer vision-based approaches. Within this new framework, we directly reduce the number of false alarms by testing if the detected events are due to characteristic background motions. In addition, we introduce a new dataset suitable for the evaluation of dynamic background detection. It consists of real-world events detected by a commercial surveillance system from two static surveillance cameras. The research question we address is whether dynamic background can be detected reliably and efficiently using simple motion features and in the presence of similar but meaningful events such as loitering. Inspired by the tree aerodynamics theory, we propose a novel method named local variation persistence (LVP), that captures the key characteristics of swaying motions. The method is posed as a convex optimization problem whose variable is the local variation. We derive a computationally efficient algorithm for solving the optimization problem, the solution of which is then used to form a powerful detection statistic. On our newly collected dataset, we demonstrate that the proposed LVP achieves excellent detection results and outperforms the best alternative adapted from existing art in the dynamic background literature.

Determining and classifying pathological human sounds are still an interesting area of research in the field of speech processing. This paper explores different methods of voice features extraction, namely: Mel frequency cepstral... more

Determining and classifying pathological human sounds are still an interesting area of research in the field of speech processing. This paper explores different methods of voice features extraction, namely: Mel frequency cepstral coefficients (MFCCs), zero-crossing rate (ZCR) and discrete wavelet transform (DWT). A comparison is made between these methods in order to identify their ability in classifying any input sound as a normal or pathological voices using support vector machine (SVM). Firstly, the voice signal is processed and filtered, then vocal features are extracted using the proposed methods and finally six groups of features are used to classify the voice data as healthy, hyperkinetic dysphonia, hypokinetic dysphonia, or reflux laryngitis using separate classification processes. The classification results reach 100% accuracy using the MFCC and kurtosis feature group. While the other classification accuracies range between~60% to~97%. The Wavelet features provide very good classification results in comparison with other common voice features like MFCC and ZCR features. This paper aims to improve the diagnosis of voice disorders without the need for surgical interventions and endoscopic procedures which consumes time and burden the patients. Also, the comparison between the proposed feature extraction methods offers a good reference for further researches in the voice classification area.

The ability for automated technologies to correctly identify a human's actions provides considerable scope for systems that make use of human-machine interaction. Thus, automatic 3D Human Action Recognition is an area that has seen... more

The ability for automated technologies to correctly identify a human's actions provides considerable scope for systems that make use of human-machine interaction. Thus, automatic 3D Human Action Recognition is an area that has seen significant research effort. In work described here, a human's everyday 3D actions recorded in the NTU RGB+D dataset are identified using a novel structured-tree neural network. The nodes of the tree represent the skeleton joints, with the spine being represented by the root. The connection between a child node and its parent is known as the incoming edge while the reciprocal connection is known as the outgoing edge. The uses of tree structure lead to a system that intuitively maps to human movements. The classifier uses the change in displacement of joints and change in the angles between incoming and outgoing edges as features for classification of the actions performed.

The use of two dimensional (2-D) continuous wavelet analysis has not been extensive for image processing using wavelets. It has been overshadowed by the 2-D discrete dyadic wavelet transform (DWT) due to its compactness and excellent... more

The use of two dimensional (2-D) continuous wavelet analysis has not been extensive for image processing using wavelets. It has been overshadowed by the 2-D discrete dyadic wavelet transform (DWT) due to its compactness and excellent performance in coding, data compression, image reconstruction, etc. However, the 2-D DWT has some restrictions on the scale and position parameters, and it does not detect all the features of an image unless properly tuned. The 2-D continuous wavelet transform (CWT), on the other hand, is more flexible and provides complete control over the scale and position parameters; and thus it is capable of extracting various features of an image, which cannot be accomplished by the DWT.

This paper presents a novel concept for controlling the consumer devices such as MP3 player or other daily life appliances by fusion of eye gaze and gesture recognition methodologies. Such system is deployable for virtually controlling... more

This paper presents a novel concept for controlling the consumer devices such as MP3 player or other daily life appliances by fusion of eye gaze and gesture recognition methodologies. Such system is deployable for virtually controlling the consumer devices anywhere in the home and office. The usability of the system is also tested with patients at the intensive care units of the hospitals where the patients may not able to operate the consumer devices in a regular way. The proposed system consists of a video processing based embedded system, a CCD camera and situated display. Physical control options are displayed over the situated display. Selection / de-selection process of displayed control option over situated display is accomplished by analyzing the video sequence captured by the CCD camera. Eye gaze estimation and head gesture recognition algorithms analyze the video sequence and reveal the control command that has to be sent to the infotainment or other consumer devices.

Background and objective: Accurate, reliable, efficient, and precise measurements of the lumen geom- etry of the common carotid artery (CCA) are important for (a) managing the progression/regression of atherosclerotic build-up and (b) the... more

Background and objective: Accurate, reliable, efficient, and precise measurements of the lumen geom- etry of the common carotid artery (CCA) are important for (a) managing the progression/regression of atherosclerotic build-up and (b) the risk of stroke. The image-based degree of stenosis in the carotid artery and the plaque burden can be predicted using the automated carotid lumen diameter (LD)/inter- adventitial diameter (IAD) measurements from B-mode ultrasound images. The objective of this review is to present the state-of-the-art methods and systems for the measurement of LD/IAD in CCA based on automated or semi-automated strategies. Further, the performance of these systems is compared based on various metrics for its measurements. Methods: The automated algorithms proposed for the segmentation of carotid lumen are broadly classi- fied into two different categories as: region-based and boundary-based. These techniques are discussed in detail specifying their pros and cons. Further, we discuss the challenges encountered in the segmen- tation process along with its quantitative assessment. Lastly, we present stenosis quantification and risk stratification strategies. Results: Even though, we have found more boundary-based approaches compared to region-based ap- proaches in the literature, however, the region-based strategy yield more satisfactory performance. Novel risk stratification strategies are presented. On a patient database containing 203 patients, 9 patients are identified as high risk patients, whereas 27 patients are identified as medium risk patients. Conclusions: We have presented different techniques for the lumen segmentation of the common carotid artery from B-mode ultrasound images and measurement of lumen diameter and inter-adventitial di- ameter. We believe that the issue regarding boundary-based techniques can be compensated by taking regional statistics embedded with boundary-based information.

Sports video analysis has received special attention from researchers due to its high popularity and general interest on semantic analysis. Hence, soccer videos represent an interesting field for research allowing many types of... more

Sports video analysis has received special attention from researchers due to its high popularity and general interest on semantic analysis. Hence, soccer videos represent an interesting field for research allowing many types of applications: indexing, summarization, players' behavior recognition and so forth. Many approaches have been applied for field extraction and recognition, arc and goalmouth detection, ball and players tracking, and high level techniques such as team tactics detection and soccer models definition. In this paper, we provide an hierarchy and we classify approaches into this hierarchy based on their analysis level, i.e., low, middle, and high levels. An overview of soccer event identification is presented and we discuss general issues related to it in order to provide relevant information about what has been done on soccer video processing.

Recensione del volume:
Arcagni Simone, L’occhio macchina. Uno sguardo sulla vita algoritmica, Einaudi, Torino, 2018

In this paper, we explore some of the applications of computer vision to sports analytics. Sport analytics deals with understanding and discovering patterns from a corpus of sports data. Analysing such data provides important performance... more

In this paper, we explore some of the applications of computer vision to sports analytics. Sport analytics deals with understanding and discovering patterns from a corpus of sports data. Analysing such data provides important performance metrics for the players, for instance in soccer matches, that could be useful for estimating their fitness and strengths. Team level statistics can also be estimated from such analysis. This paper mainly focuses on some the challenges and opportunities presented by sport video analysis in computer vision. Specifically, we use our multi-camera setup as a framework to discuss some of the real-life challenges for machine learning algorithms.

Abandoned Object Detection is one of the important tasks in video surveillance system. This paper proposes a work related to automatic detection of abandoned and unknown objects using background subtraction, morphological operation and... more

Abandoned Object Detection is one of the important tasks in video surveillance system. This paper proposes a work related to automatic detection of abandoned and unknown objects using background subtraction, morphological operation and centroid method. The aim of the approach is to automatically recognize activities around restricted area to improve safety and security of the servicing area. The system takes as input from the camera, tracking and recognition results and fuses these into object estimation. A proposed algorithm for object tracking in video, based on image segmentation is proposed. With the image segmentation all objects in video can be detected whether they are moving or not by using segmentation results of successive frames. Consequently, the proposed algorithm can be applied to multiple movements.The algorithm was tested on real time video surveillance system and it produces very low false alarms and missing detection. This approach definitely provides security and detects the moving object in real time video sequence and live video streaming.
Qualitative and quantitative results in terms of Detection Rate (DR), False Alarm Rate (FAR), success rate and aver-age processing time per frame are given. The proposed algorithms are compared with the established methods based on simple difference and background subtraction.
Index Terms— AOD-abandoned object detection, OpenCV, action detection, suspicious event detection, histogram equalization, DR, FAR, success Rate.

In this paper, we made a comprehensive study to observe critically the performance of DCT-IFDMA aided SC-FDMA wireless communication system on video signal transmission. The 4×4 dual polarized multi antenna... more

In this paper, we made a
comprehensive study to observe critically the
performance of DCT-IFDMA aided SC-FDMA
wireless communication system on video signal
transmission. The 4×4 dual polarized multi
antenna supported system utilizes various useful
digital signal processing schemes such as BLUE,
Q-less QR decomposition, 2D Median Filtering,
Repeat and Accumulate (RA). It is observable from
MATLAB based simulative study that the system
shows quite acceptable and satisfactory
performance in retrieving transmitted video signal
under scenario of flat fading channel with
impulsive noise contamination environment for
the specific case of implementing BLUE signal
detection, QAM digital modulation and Repeat and
Accumulate channel coding scheme.

This paper presents a framework for soccer event detection through collaborative analysis of the textual, visual and aural modalities. The basic notion is to decompose a match video into smaller segments until ultimately the desired... more

This paper presents a framework for soccer event detection through collaborative analysis of the textual, visual and aural modalities. The basic notion is to decompose a match video into smaller segments until ultimately the desired eventful segment is identified. Simple features are considered namely the minute-by-minute reports from sports websites (i.e., text), the semantic shot classes of far and closeup-views (i.e., visual), and the low-level features of pitch and log-energy (i.e., audio). The framework demonstrates that despite considering simple features, and by averting the use of labeled training examples,
event detection can be achieved at very high accuracy. Experiments conducted on ~30-hours of soccer video show very promising results for the detection of goals, penalties, yellow cards and red cards.

In Movie Recommender Systems, when a new user registers to the system and she has not yet provided any information about her, the system may not be able to generate personalized recommendations for that user. In such a Cold Start... more

In Movie Recommender Systems, when a new user registers to the system and she has not yet provided any information about her, the system may not be able to generate personalized recommendations for that user. In such a Cold Start situation, many real-world recommender systems suggest popular movies to the new user. Such movies are very likely to be interesting to the new users. A very common approach for measuring the movie popularity is based on counting the number of ratings (as user votes) provided by a community of the existing users. However, in certain cases, we cannot properly measure the popularity of the movies with this common approach. This paper proposes a novel method for predicting the popularity of movies. The method is based on hybrid visually-driven features, representative of the movie content, which can be used to effectively predict not only the movie popularity but also the average rating of the movie. Our extensive experiments on a large dataset of more than 13'000 movies trailers show that the proposed hybrid approach achieves promising results by exploiting visual Attractiveness features of movies in comparison to the other baseline features.

finding parking availability for a specific time period is a very tedious job in urban areas. T he Indian government now focusing on t he smart city project, already they published city name for a n upcoming smart city project. In smart... more

finding parking availability for a specific time period is
a very tedious job in urban areas. T he Indian government now
focusing on t he smart city project, already they published city
name for a n upcoming smart city project. In smart city
application , intelligent transportation system (ITS) plays an
important role- in that finding parking place, specifically for the
car owner to avoid time computation, as well as congestion in traffic is going to be very important. In this article, we propose
an intelligent car parking system for the smart city using Circle
Hough Transform (CHT)

This paper focuses on methods applied for sign language video processing. In the first part, we present a robust traking method which detects and tracks the hands and face of a person performing Signs' language communication. The... more

This paper focuses on methods applied for sign language video processing. In the first part, we present a robust traking method which detects and tracks the hands and face of a person performing Signs' language communication. The method uses a model of skin color and three particle filters to track the two hands and the face, with re-sampling and annealed

Recently inter-specific hybridization is a common phenomenon in fresh water fish's species. Natural hybridization is more common in fish than in other vertebrates, and non-native fish species which have been introduced extensive in a... more

Recently inter-specific hybridization is a common phenomenon in fresh water fish's species. Natural hybridization is more common in fish than in other vertebrates, and non-native fish species which have been introduced extensive in a worldwide those are difficult to identify manually. However, inter specific hybridize among genetically divergent fish are often fertile, and provide good product that results in creation of survival fit species. In case of this nowadays a lot of works were done by depending on the computer in order to processing time to be reduced when the experts pass a key decision what type of fish species exist in under marine area as biologist and agricultural researcher. Due to this computer has been used for digital image recognition which has been extremely found and studied for this role work to get fast response of replied when it has been compared and contrast with human know how knowledge level with recent machine level knowledge one which has been depending on computer and provide more results which are accurate. Even though due to hybridization the agricultural experts has been faced a challenges and confusion to isolate and clearly tries to identify as well as recognize this occurring species based on morphological shapes and texture of fish species images. So that using these procedural techniques the researcher work provide attractive fish recognition based on their types of species. The detection, recognition and classification system is using the proposed procedural methods. Those procedural methods image processing approaches such as noise removal, image enhancement, image restoration, feature extraction, segmentation, filtering, histogram processing, countor tracking, edge detection, graye scale processing, Hsv color fish image based processing. Beside this, the study used Svm to classify and recognized those fish's species using the interspecific values with a common morphological fish image shape and texture that the fish contained. This work scientifically contributed to recognize and classify that those complex interbreed fish gene type using feature extraction based on their International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 07 Issue: 01 | Jan 2020 www.irjet.net p-ISSN: 2395-0072 © 2020, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 2 image's shape and texture values. In this work the detection system, which provides the fish characterization for recognition purposes were proposed. Performance evaluation is possible done to achieve satisfying detection accuracy 96.77424% for two used datasets which are training and test data set those are performed based on their fish local data set images with five species which are collected through techno w2 phone. Generally in this research work there are a major challenges and future works which the researcher recommended and suggested as future works are identify the most promising fish classification/ detection algorithms that used CCTv camera rather than mobile camera. As future the researcher ready to preparing public Ethiopia national fish data set which used various algorithms like Bayesian classifier which used mean standard average values.

Developing intelligent systems to prevent car accidents can be very effective in minimizing accident death toll. One of the factors which play an important role in accidents is the human errors including driving fatigue relying on new... more

Developing intelligent systems to prevent car accidents can be very effective in minimizing accident death toll. One of the factors which play an important role in accidents is the human errors including driving fatigue relying on new smart techniques; this paper detects the signs of fatigue and sleepiness in the face of

The digital humanities have been very successful in proposing quantitative methods for the analysis of textual data. However, similar methods are not widespread for the study of artistic expressions that rely on motion (such as theatre).... more

The digital humanities have been very successful in proposing quantitative methods for the analysis of textual data. However, similar methods are not widespread for the study of artistic expressions that rely on motion (such as theatre). In order to develop a more robust, quantitative approach to the study of motion in theatre performances, we use video processing techniques to analyze a puppet theatre recording from Indonesia. By calculating the average speed of the different scenes, we found that there is a strong correspondence between the narrative structure and the speed of the puppets. We hope this work contributes to a development of quantitative analysis methods for the study of theatre and that it also impacts the way in which theatre documentation projects are carried

More than 2 million people in the United States are unable to speak or use handwriting as an effective and efficient mean of communication (ASHA,2004). This paper discusses a brief history of augmentative alternative communication (AAC)... more

Autonomous vehicles make use of sensors to perceive the world around them, with heavy reliance on vision-based sensors such as RGB cameras. Unfortunately, since these sensors are affected by adverse weather, perception pipelines require... more

Autonomous vehicles make use of sensors to perceive the world around them, with heavy reliance on vision-based sensors such as RGB cameras. Unfortunately, since these sensors are affected by adverse weather, perception pipelines require extensive training on visual data under harsh conditions in order to improve the robustness of downstream tasks - data that is difficult and expensive to acquire. Based on GAN and CycleGAN architectures, we propose an overall (modular) architecture for constructing datasets, which allows one to add, swap out and combine components in order to generate images with diverse weather conditions. Starting from a single dataset with ground-truth, we generate 7 versions of the same data in diverse weather, and propose an extension to augment the generated conditions, thus resulting in a total of 14 adverse weather conditions, requiring a single ground truth. We test the quality of the generated conditions both in terms of perceptual quality and suitability for training downstream tasks, using real world, out-of-distribution adverse weather extracted from various datasets. We show improvements in both object detection and instance segmentation across all conditions, in many cases exceeding 10 percentage points increase in AP, and provide the materials and instructions needed to re-construct the multi-weather dataset, based upon the original Cityscapes dataset.

Various investigations show that driver's drowsiness is one of the main causes of road accidents. The development of technologies for preventing drowsiness at the time is a major challenge in the field of accident avoidance. The advance... more

Various investigations show that driver's drowsiness is one of the main causes of road accidents. The development of technologies for preventing drowsiness at the time is a major challenge in the field of accident avoidance. The advance in computing technology has provided the means for building intelligent vehicle systems. The purpose of this study is to detect the drowsiness in drivers to prevent the accidents and to improve the safety on the highways.
A system aiming at detecting driver drowsiness or fatigue on the basis of video analysis is presenting. A real time face detection is implemented to locate driver's face region. A method of detecting drowsiness in drivers is developed by using a camera that points directly towards the face and capture for the video. As a detection method the system uses image processing technology to analyze the images of the driver's face taken with a video camera. The captured video is done; it is converted into number of frames of images and monitoring of the face region and eyes in order to detect drowsiness. The system is able monitoring eyes and determines whether the eyes are in an open or shows signs of drowsiness. This detection system avoids a noncontact technique for judging various levels of alertness and facilities early detection of a decline in alertness during driving.

Using smart parking systems has become very important, and particularly so for metropolitan areas, because of the benefits for drivers in many aspects, such as time, frustration, stress, and anger, in addition to the increased consumption... more

Using smart parking systems has become very important, and particularly so for metropolitan areas, because of the benefits for drivers in many aspects, such as time, frustration, stress, and anger, in addition to the increased consumption of fuel while searching for a vacant parking space. This paper proposes a review of recent advances in sensing and communication technology concerning smart parking systems. It includes a brief study of the selected topics and provides an implementation process of those selected systems. Moreover, this work proposes a design approach for a smart car parking system prototype based on utilizing CCTVs (nodes), it is also illustrates the algorithms used for computer vision detection through simulation and real environments, as the system has been deployed in both these environments. Furthermore, the system has been tested and evaluated by stakeholders via a user-centred design process by applying a qualitative research; the promising results demonstrate the effectiveness of our prototype. Finally, this paper discusses the benefits of engaging the stakeholders to develop the prototype.

- LAURA ÁLVAREZ BENÍTEZ IRISH LEGENDS: THE CHILDREN OF LIR THE MOUSETRAP. AGATHA CHRISTIE. READING GUIDE 09 – 18 20 – 38 - ESTHER MANSILLA RODRÍGUEZ LA ENTREVISTA MOTIVACIONAL EN TUTORÍA 40 – 50 - ANTONIO DADER GARCÍA EL SISTEMA DIÉDRICO... more

- LAURA ÁLVAREZ BENÍTEZ
IRISH LEGENDS: THE CHILDREN OF LIR
THE MOUSETRAP. AGATHA CHRISTIE. READING GUIDE
09 – 18
20 – 38
- ESTHER MANSILLA RODRÍGUEZ
LA ENTREVISTA MOTIVACIONAL EN TUTORÍA
40 – 50
- ANTONIO DADER GARCÍA
EL SISTEMA DIÉDRICO DIRECTO EN LAS PRUEBAS DE ACCESO A LA UNIVERSIDAD
52 – 62
- ESTER ROMERO CABALLERO
LA IMPORTANCIA DE LA METODLOGÍA CLIL EN LA EDUCACIÓN BILINGÜE
64 – 75
- IVÁN GUERRERO VAQUERIZO
INTRODUCCIÓN A LA COMPRESIÓN DE VÍDEO BASADA EN REDUNDANCIAS
77 – 87

Downloading subtitles is often complicated as most video platforms do not allow to download the transcripts. With a newly web service http://ccSubs.com this is now easily possible. The user just has to provide the link to a video and the... more

Downloading subtitles is often complicated as most video platforms do not allow to download the transcripts. With a newly web service http://ccSubs.com this is now easily possible. The user just has to provide the link to a video and the ccSubs service let’s it download all subtitles or closed captions in an easy way.

Tvorba videí sa v dnešnej dobe stala veľmi obľúbenou činnosťou. Dostupnosť techniky a softvéru, možnosť prezentovať sa na internete a aj spôsob, ako si zlepšiť finančnú situáciu spôsobuje, že veľa mladých ľudí táto činnosť láka. Skôr, ako... more

Tvorba videí sa v dnešnej dobe stala veľmi obľúbenou činnosťou.
Dostupnosť techniky a softvéru, možnosť prezentovať sa
na internete a aj spôsob, ako si zlepšiť finančnú situáciu spôsobuje,
že veľa mladých ľudí táto činnosť láka.
Skôr, ako sa niekto pustí do tvorby prvých videí, ktoré nemajú
ostať len v jeho počítači, mal by poznať, čo všetko táto práca
so sebou prináša, čo k nej bude potrebovať a čo treba vedieť.
Preto sme sa rozhodli vytvoriť metodické materiály pozostávajúce
z učebnice a doplnkových edukačných materiálov určených
nielen na výučbu predmetu Audiovizuálna tvorba na
Fakulte masmediálnej komunikácie UCM v Trnave, ale aj pre
všetkých, ktorí sa chcú venovať audiovizuálnej tvorbe.
Tieto materiály obsahujú teoretický základ z oblasti audiovizuálnej
tvorba, postupy pri vytváraní audiovizuálnych obsahov
(proces tvorby scenára, práca s kamerou, problematika strihu,
zvuková stránka, atď.), a tiež krátke videonávody k spomenutým
útvorom, úlohy a cvičenia.
Učebnica s doplnkovými materiálmi predstavuje úvod do tvorby
audiovizuálneho diela pre začiatočníkov, a preto je vhodná
na vyučovanie spomínaného predmetu. Je rozdelená do troch
častí: Predprodukcia, Produkcia a Postrodukcia.
Veríme, že učebnica bude vyhľadávanou pomôckou a základom
pre tvorbu nových a kvalitných audiovizuálnych diel.

As a partner in the Centre for Digital Video Processing, the Visual Media Processing Group at Dublin City University conducts research and development in the area of digital video management. The current stage of development is... more

As a partner in the Centre for Digital Video Processing, the Visual Media Processing Group at Dublin City University conducts research and development in the area of digital video management. The current stage of development is demonstrated on our Web-based digital video system called Físchlár [1,2], which provides for efficient recording, analyzing, browsing and viewing of digitally captured television programmes. In order to make the browsing of programme material more efficient, users have requested the option of automatically deleting advertisement breaks. Our initial work on this task focused on locating ad-breaks by detecting patterns of silent black frames which separate individual advertisements and/or complete ad-breaks in most commercial TV stations. However, not all TV stations use silent, black frames to flag ad-breaks. We therefore decided to attempt to detect advertisements using the rate of shot cuts in the digitised TV signal. This paper describes the implementation and performance of both methods of ad-break detection.

The aim of this work is to solve the unit commitment (UC) problem in power systems by calculating minimum production cost for the power generation and finding the best distribution of the generation among the units (units scheduling)... more

The aim of this work is to solve the unit commitment (UC) problem in power systems by calculating minimum production cost for the power generation and finding the best distribution of the generation among the units (units scheduling) using binary grey wolf optimizer based on particle swarm optimization (BGWOPSO) algorithm. The minimum production cost calculating is based on using the quadratic programming method and represents the global solution that must be arriving by the BGWOPSO algorithm then appearing units status (on or off). The suggested method was applied on "39 bus IEEE test systems", the simulation results show the effectiveness of the suggested method over other algorithms in terms of minimizing of production cost and suggesting excellent scheduling of units.

In this paper, we identify QoS control challenges for multimedia consumer terminals, starting from a brief description of an application execution model and a QoS resource management framework. In the context of this framework, we... more

In this paper, we identify QoS control challenges for multimedia consumer terminals, starting from a brief description of an application execution model and a QoS resource management framework. In the context of this framework, we recapitulate earlier work aimed at QoS control for a soft real-time scalable video processing task. To identify QoS control challenges, we take a closer look at the framework, our initial QoS control approach, and the controlled video