Computer Vision Research Papers - Academia.edu (original) (raw)

One aspect of a growing VR industry that developers have to face is the ethics behind the technology. This includes making sure that technology is readily available and accessible to as large of a population as possible. Current consumer... more

One aspect of a growing VR industry that developers have to face is the ethics behind the technology. This includes making sure that technology is readily available and accessible to as large of a population as possible. Current consumer virtual reality (VR) headsets typically utilize two controllers to navigate a virtual environment, leading to accessibility issues for potential users that cannot effectively operate a controller. We propose NaVRgate, a proof of concept idea that removes the need for controllers in which a user uses expressions to navigate a virtual environment. The system utilizes the computer webcam and computer vision face and eye position tracking to capture the nature of expression tracking, with certain positional thresholds representing different facial expressions. To test this system, We design a game environment where a user navigates with either a controller or the face position tracker, collecting a set of orbs scattered around the map as quickly as they can, comparing the efficiency between navigation through the novel computer vision and traditional controller methods. Users are also questioned on the difficulty of use and experience with each control input method. This paper details the process of the development and drafts, to the statistical experiment constructed to determine the efficiency of head gestures.

Plants are fundamentally important to life. Key research areas in plant science include plant species identification, weed classification using hyper spectral images, monitoring plant health and tracing leaf growth, and the semantic... more

Plants are fundamentally important to life. Key research areas in plant science include plant species identification, weed classification using hyper spectral images, monitoring plant health and tracing leaf growth, and the semantic interpretation of leaf information. Botanists easily identify plant species by discriminating between the shape of the leaf, tip, base, leaf margin and leaf vein, as well as the texture of the leaf and the arrangement of leaflets of compound leaves. Because of the increasing demand for experts and calls for biodiversity, there is a need for intelligent systems that recognize and characterize leaves so as to scrutinize a particular species, the diseases that affect them, the pattern of leaf growth, and so on. We review several image processing methods in the feature extraction of leaves, given that feature extraction is a crucial technique in computer vision. As computers cannot comprehend images, they are required to be converted into features by individually analyzing image shapes, colors, textures and moments. Images that look the same may deviate in terms of geometric and photometric variations. In our study, we also discuss certain machine learning classifiers for an analysis of different species of leaves.

7th International Conference on Artificial Intelligence and Applications (AI 2021) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence and its... more

7th International Conference on Artificial Intelligence and Applications (AI 2021) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence and its applications. The Conference
looks for significant contributions to all major fields of the Artificial Intelligence, Soft Computing in theoretical and practical aspects. The aim of the Conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and
share cutting-edge development in the field. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to.

Abstract—CAMTUAL: An interactive mobile app to research fundamental aspects of deep learning technologies to support Smartphones users a 2D-to-3D automatic converter using smartphones built-in cameras. The whole idea inspired by MagicToon... more

Abstract—CAMTUAL: An interactive mobile app to research fundamental aspects of deep learning technologies to support Smartphones users a 2D-to-3D automatic converter using smartphones built-in cameras. The whole idea inspired by MagicToon App [1]. As 3D video viewing becomes important and virtual reality market started, the request for 3D devices and contents is growing faster. Producing 3D videos, still remains as a big challenge. In this paper we presented a mobile app that uses a 3D deep neural networks algorithm to automatically convert 2D video and images to a stereoscopic 3D format [2]. In comparison to other mobile apps that doesn’t use automatic 2D-to-3D conversion algorithms, our mobile app uses method that trained end-to-end automatically on stereo pairs extracted from existing 3D videos. This novel mobile app approach outperforms baselines in human evaluations and quantitative.

The International Journal of Artificial Intelligence & Applications (IJAIA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Artificial Intelligence & Applications... more

The International Journal of Artificial Intelligence & Applications (IJAIA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Artificial Intelligence & Applications (IJAIA). It is an international journal intended for professionals and researchers in all fields of AI for researchers, programmers, and software and hardware manufacturers. The journal also aims to publish new attempts in the form of special issues on emerging areas in Artificial Intelligence and applications.

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.

A method is presented for the recovery of optical flow. The key idea is that the local spatial structure of optical flow, with the exception of surface boundaries, is usually rather coherent and can thus be appropriately approximated by a... more

A method is presented for the recovery of optical flow. The key idea is that the local spatial structure of optical flow, with the exception of surface boundaries, is usually rather coherent and can thus be appropriately approximated by a linear vector field. According to the proposed method, the optical flow components and their first order spatial derivatives are computed

In this paper an unsupervised colour image segmentation algorithm is presented. This method combines the advantages of the approaches based on split&merge and region growing, and the use of the RGB and HSV colour representation... more

In this paper an unsupervised colour image segmentation algorithm is presented. This method combines the advantages of the approaches based on split&merge and region growing, and the use of the RGB and HSV colour representation models. The effectiveness of the proposed method has been verified by the implementation of the algorithm using three different testing images with homogeneous regions, spatially compact and continuous. It was observed that the proposed algorithm outperforms the other analysed techniques requiring shorter processing time when compared with the other analysed methods.

In this paper we propose to develop a device that can be used by the visually challenged to read normal English books. Here we focus on letter-by-letter segmentation, recognition and transliteration to the Braille format. The device would... more

In this paper we propose to develop a device that can be used by the visually challenged to read normal English books. Here we focus on letter-by-letter segmentation, recognition and transliteration to the Braille format. The device would use on board software to do the recognition and conversion. The recognized characters are transmitted to the interface which converts the characters to the Braille format which can be felt-read by the visually challenged. The device would be cheaper among its counterparts.

Finite element models of current structures often behave differently than the structure itself. Model updating techniques are used to enhance the capabilities of the numerical model such that it behaves like the real structure.... more

Finite element models of current structures often behave differently than the structure itself. Model updating techniques are used to enhance the capabilities of the numerical model such that it behaves like the real structure. Experimental data is used in model updating techniques to identify the parameters of the numerical model. In civil infrastructure these model updating techniques use either static or dynamic measurements, separately. This paper studies how a Bayesian updating framework behaves when both static and dynamic data are used to updated the model. Displacements at specific structure locations are obtained for static tests using a computer vision method. High density mode shapes and natural frequencies are obtained using a moving accelerometer structure. The static data and the modal characteristics are combined in a Bayesian modal updating technique that accounts for the incompleteness and uncertainty of the data as well as the possible nonuniqueness of the solution. Results show how the posterior probability density function changes when different type of information is included for updating.

Perception techniques in novel times have enormously improved in autonomously and accurately predicting the ultimate states of the delivery robots. The precision and accuracy in recent research lead to high computation costs for... more

Perception techniques in novel times have enormously improved in autonomously and accurately predicting the ultimate states of the delivery robots. The precision and accuracy in recent research lead to high computation costs for autonomous locomotion and expensive sensors and server dependency. Low computational algorithms for delivery robots are more viable as compared to pipelines used in autonomous vehicles or prevailing delivery robots. A blend of different autonomy approaches, including semantic segmentation, obstacle detection, obstacle tracking, and high fidelity maps, is presented in our work. Moreover, LCPP comprises low computational algorithms feasible on embedded devices with algorithms running more efficiently and accurately. Research also analyzes state-of-the-art algorithms via practical applications. Low computational algorithms have a downside of accuracy, which is not as proportional as computation. Finally, the study proposes that this algorithm will be more realizable as compared to Level 5 autonomy for delivery robots.

In this paper, we propose a neural network model for human emotion and gesture classification. We demonstrate that the proposed architecture represents an effective tool for real-time processing of customer's behavior for distributed... more

In this paper, we propose a neural network model for human emotion and gesture classification. We demonstrate that the proposed architecture represents an effective tool for real-time processing of customer's behavior for distributed on-land systems, such as information kiosks, automated cashiers and ATMs. The proposed approach combines most recent biometric techniques with the neural network approach for real-time emotion and behavioral analysis. In the series of experiments, emotions of human subjects were recorded, recognized, and analyzed to give statistical feedback of the overall emotions of a number of targets within a certain time frame. The result of the study allows automatic tracking of user’s behavior based on a limited set of observations.

It is common practice to utilize evidence from biological and psychological vision experiments to develop computational models for low-level feature extraction. The receptive profiles of simple cells in mammalian visual systems have been... more

It is common practice to utilize evidence from biological and psychological vision experiments to develop computational models for low-level feature extraction. The receptive profiles of simple cells in mammalian visual systems have been found to closely resemble Gabor filters. ...

Visual impairment and blindness caused by infectious diseases has been greatly reduced, but increasing numbers of people are at risk of age-related visual impairment. Visual information is the basis for most navigational tasks, so... more

Visual impairment and blindness caused by infectious diseases has been greatly reduced, but increasing numbers of people are at risk of age-related visual impairment. Visual information is the basis for most navigational tasks, so visually impaired individuals are at disadvantage because appropriate information about the surrounding environment is not available. With the recent advances in inclusive technology it is possible to extend the support given to people with visual impairment during their mobility. In this context we propose a system, named SmartVision, whose global objective is to give blind users the ability to move around in unfamiliar environments, whether indoor or outdoor, through a user friendly interface. This paper is focused mainly in the development of the computer vision module of the SmartVision system.