Object Recognition Basics and Visual Surveillance (original) (raw)
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1 Object Recognition Basics and Visual Surveillance
2014
In this report basic principles of object recognition techniques are described and also some of the visual surveillance applications are given as examples of different techniques. In our study, suitable recognition techniques will be used for the traffic characterization of recognized images for wireless multimedia sensor networks. Today object recognition is one of the popular topics and takes more attention day by day. There is a wide application area for object recognition fields like industry (quality control etc.), medical image possessing, and military applications for instance, in the field
Image Recognition Traffic Patterns for Wireless Multimedia Sensor Networks
2008
The objective of this work is to identify some of the traffic characteristics of Wireless Multimedia Sensor Networks (WMSN). Applications such as video surveillance sensor networks make use of new paradigms related with computer vision and image processing techniques. These sensors do not send whole video sequences to the wireless sensor network, but objects of interest detected by the camera. In order to able to design appropriate networking protocols, a better understanding of the traffic characteristics of these multimedia sensors is needed. In this work, we analyze the traffic differences between cameras that send whole coded images and those that first process and recognize objects of interest using Object Recognition techniques.
Object Detection and Identification in Surveillance Images using Image Processing
International Journal of Engineering and Advanced Technology, 2019
The goal of object detection and identification in surveillance images using image processing is to detect a particular part of the image from surveillance camera like an object’s position, movement, and its sequence. Object tracking and recognition deal with recognizing the image of video which can differ in color, range, size, illumination changes with time and some cluttered images. As this paper has been surveying and an algorithm has been proposed and implemented, the identified object has freed from the shadow, clutter, illumination changes were detected and eliminated appropriately.
International Journal for Research in Applied Science & Engineering Technology (IJRASET), 2023
Thefts have increased over the past few years. This creates a dangerous climate where people live in fear. Issues with home security are a worry in the current atmosphere. The current generation of intrusion detection systems is very expensive and prone to false alarms. Open CV and mobile devices are used to find a solution to this issue. Intruders can be precisely detected using this framework, which filters the motion of moving objects. An API by the name of Twilio will notify the user when an intrusion is made, and the video will be saved locally. This application's main purpose is to act as a surveillance system that can identify persons, recognise faces, and display user information. This lowers the possibility of future system penetration by people. This project gathers camera photos and using image comparison methods to identify intruders using the Open CV library. The streamed video will be delivered from the server to the remote administrator via the Android phone if an intrusion is found after comparison. The administrator can then take the necessary steps and locally notify her security. Users are notified by MMS, SMS, or email when notifications are sent and pertinent data is recorded. able to display videos relevant to the user. This approach improves social stability, keeps your house secure, and lowers burglaries.
Video cameras are becoming a ubiquitous feature of modern life, useful for surveillance, crime prevention, and forensic evidence. We cannot solely rely upon human efforts to watch and shift through hundreds and thousands of video frames for crime alerts and forensic analysis. That is a non-scalable task. We need a semi-automated video analysis and event recognition system that can provide timely warnings to alert security personnel, and that can substantially reduce the search space for forensic analysis tasks. This survey describes the approach of wireless intelligent video surveillance system using moving object recognition technique.
Image analysis architectures and techniques for intelligent surveillance systems
Iee Proceedings-vision Image and Signal Processing, 2005
Video security is becoming more and more important today, as the number of installed cameras can attest. There are many challenging commercial applications to monitor people or vehicle traffic. The work reported here has both research and commercial motivations. Our goals are first to obtain an efficient intelligent system that can meet strong industrial surveillance system requirements and therefore be real-time, distributed, generic and robust. Our second goal is to have a development platform that allows researchers to conceive and easily test new vision algorithms thanks to its modularity and easy set-up.
Video Image Processing For Traffic Analysis
Jurnal Teknologi, 1992
In recent years the application of computer-based image processing techniques to a range of traffic data collection tasks has been successfully demonstrated. In a similar field of research carried out by the author at the University of Wales College of Cardiff, a system based on commercial image processing hardware, a 80486 IBM PC-AT and a video recorder was assembled. The main aim was to develop a system for automatic vehicle data measurement and to extend its application to the collection and analysis of pedestrian data. This paper will focus on the development of the system for vehicle detection and measurement. A direct segmentation technique on the video images was adopted as a standard method of vehicle identification. The identification of the presence of an individual vehicle based on brightness information at relatively few sample points within the images was possible. Double threshold values were applied to the area of interest for the conversion of the area into a binary ...
Real-time object detection in embedded video surveillance systems
In this paper we report a new method to detect both moving objects and new stationary objects in video sequences. On the basis of temporal consideration we classify pixels into three classes: background, midground and foreground to distinguish between long-term, medium-term and shortterm changes. The algorithm has been implemented on a hardware platform with limited resources and it could be used in a wider system like a wireless sensor networks. Particular care has been put in realizing the algorithm so that the limited available resources are used in an efficient way. Experiments have been conducted on publicly available datasets and performance measures are reported.
International Journal of Innovative Research in Computer and Communication Engineering, 2015
Machine-controlled motion detection technology is Associate in nursing integral element of intelligent transportation systems, and is especially essential for management of traffic and maintenance of traffic police investigation systems. Traffic police investigation systems mistreatment video communication over real-world networks with restricted information measure typically encounter difficulties attributable to network congestion and/or unstable information measure. This is often particularly problematic in wireless video communication. This has necessitated the event of a rate management theme that alters the bit-rate to match the procurable network information measure, thereby manufacturing variable bit-rate video streams. However, complete and correct detection of moving objects beneath variable bit-rate video streams could be a terribly tough task. During this paper, we tend to propose Associate in nursing approach for motion detection that utilizes Associate in nursing analy...
Survey on Wireless Intelligent Video Surveillance System Using Moving Object Recognition Technology
Computer Engineering and Intelligent Systems, 2011
Video cameras are becoming a ubiquitous feature of modern life, useful for surveillance, crime prevention, and forensic evidence. We cannot solely rely upon human efforts to watch and shift through hundreds and thousands of video frames for crime alerts and forensic analysis. That is a non-scalable task. We need a semi-automated video analysis and event recognition system that can provide timely warnings to alert security personnel, and that can substantially reduce the search space for forensic analysis tasks. This survey describes the approach of wireless intelligent video surveillance system using moving object recognition technique.