Fast motion detection in coded video streams for a large-scale remote video sensor system

2014 ◽  
Author(s):  
Yong-Sung Kim ◽  
Gyu-Hee Park ◽  
Seung-Hwan Kim ◽  
Hyung-Joon Cho
Information ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 14
Author(s):  
Aluizio Rocha Neto ◽  
Thiago P. Silva ◽  
Thais Batista ◽  
Flávia C. Delicato ◽  
Paulo F. Pires ◽  
...  

In smart city scenarios, the huge proliferation of monitoring cameras scattered in public spaces has posed many challenges to network and processing infrastructure. A few dozen cameras are enough to saturate the city’s backbone. In addition, most smart city applications require a real-time response from the system in charge of processing such large-scale video streams. Finding a missing person using facial recognition technology is one of these applications that require immediate action on the place where that person is. In this paper, we tackle these challenges presenting a distributed system for video analytics designed to leverage edge computing capabilities. Our approach encompasses architecture, methods, and algorithms for: (i) dividing the burdensome processing of large-scale video streams into various machine learning tasks; and (ii) deploying these tasks as a workflow of data processing in edge devices equipped with hardware accelerators for neural networks. We also propose the reuse of nodes running tasks shared by multiple applications, e.g., facial recognition, thus improving the system’s processing throughput. Simulations showed that, with our algorithm to distribute the workload, the time to process a workflow is about 33% faster than a naive approach.


Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 219
Author(s):  
Phuoc Duc Nguyen ◽  
Lok-won Kim

People nowadays are entering an era of rapid evolution due to the generation of massive amounts of data. Such information is produced with an enormous contribution from the use of billions of sensing devices equipped with in situ signal processing and communication capabilities which form wireless sensor networks (WSNs). As the number of small devices connected to the Internet is higher than 50 billion, the Internet of Things (IoT) devices focus on sensing accuracy, communication efficiency, and low power consumption because IoT device deployment is mainly for correct information acquisition, remote node accessing, and longer-term operation with lower battery changing requirements. Thus, recently, there have been rich activities for original research in these domains. Various sensors used by processing devices can be heterogeneous or homogeneous. Since the devices are primarily expected to operate independently in an autonomous manner, the abilities of connection, communication, and ambient energy scavenging play significant roles, especially in a large-scale deployment. This paper classifies wireless sensor nodes into two major categories based the types of the sensor array (heterogeneous/homogeneous). It also emphasizes on the utilization of ad hoc networking and energy harvesting mechanisms as a fundamental cornerstone to building a self-governing, sustainable, and perpetually-operated sensor system. We review systems representative of each category and depict trends in system development.


2019 ◽  
Vol 19 (2) ◽  
pp. 56-61
Author(s):  
Mohanad Abdulhamid ◽  
Singoee Sheshai

AbstractAs a critical constituent of many associations’ protection and security precedence, video surveillance has set up its importance and benefits numerous instances with the aid of imparting immediate supervising of possessions, people, surroundings and property. This paper deals with the diagram strategy of an embedded real-time surveillance gadget based totally on Raspberry-Pi single board computer (SBC) for intruder detection which is reinforcing technology of surveillance to supply fundamental security to our life and associated control and alert operations. The suggested safety solution is hinging on our novel integration of cameras and action detectors into application of web. Raspberry-Pi is operating and controlling action detectors and video cameras for far flung sensing and surveillance, streams live video and files it for future playback. Also, this paper is focusing on growing a surveillance machine that detects strangers and to response speedily through taking pictures and relaying photos to proprietor based totally wireless module. This Raspberry-Pi based clever surveillance machine presents the concept of monitoring a region in a far-flung area. The suggested solution offers a fee advantageous ubiquitous surveillance solution, environment friendly and convenient to implement. Furthermore, the paper presents the idea of motion detection and tracking using image processing. This type of technology is of great importance when it comes to surveillance and security. Live video streams therefore be used to show how objects can be detected then tracked. The detection and tracking process are based on pixel threshold.


2011 ◽  
Vol 58-60 ◽  
pp. 2290-2295 ◽  
Author(s):  
Ruo Hong Huan ◽  
Xiao Mei Tang ◽  
Zhe Hu Wang ◽  
Qing Zhang Chen

A method of abnormal motion detection for intelligent video surveillance is presented, which includes object intrusion detection, object overlong stay detection and object overpopulation detection. Background subtraction algorithm is used to detect moving objects in video streams. Kalman filter is applied for object tracking. By the construction of relation matrix, the tracking process is divided into five statuses for prediction and estimation, which are object disappearing, object separating, new object appearing, object sheltering and object matching. The object parameters and predictive information in the next frame which is used to track moving objects is established by Kalman filter. Then, three types of abnormal motion detection are implemented. The relative position of alarm area or guard line with the rectangle boxes of the moving objects is used to detect whether the object is invading. The existing time of the moving objects in monitor area is counted to detect whether the object is staying too long. Moving objects in the monitor area are classified and counted to detect whether the objects are too much. Alarm will be triggered when abnormal motion detection as defined is detected in the monitor area.


2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Yuezhou Wu ◽  
Changjiang Liu ◽  
Shiyong Lan ◽  
Menglong Yang

Road monitoring helps to control the regional traffic situation so as to adjust the traffic flow. Real-time panorama is conducive to timely treat traffic accidents and to greatly improve traffic capacity. This paper designs a 3D road scene monitoring framework based on real-time panorama. The system is the combination of large scale panorama, satellite map textures, and 3D scene model, in which users can ramble freely. This paper has the following contributions. Firstly, land-points were extracted followed by motion detection, then comotion algorithm was applied to land-points from adjacent cameras, and homography matrix was constructed. Secondly, reference camera was chosen and transformed to overhead viewpoint; subsequently multiviews were morphed to the same viewpoint and stitched to panorama. Finally, the registration based on high-precision GPS information between 2D road panorama and 3D scene model was also proposed. The proposed framework has been successfully applied to a large road intersection monitoring. Experimental results are furnished at the end of the paper.


2009 ◽  
Vol 56 (4) ◽  
pp. 1072-1078 ◽  
Author(s):  
Yan Yu ◽  
Jinping Ou ◽  
Jun Zhang ◽  
Chunwei Zhang ◽  
Luyu Li
Keyword(s):  

2015 ◽  
Vol 27 (13) ◽  
pp. 3510-3522 ◽  
Author(s):  
Hancong Duan ◽  
Wenhan Zhan ◽  
Geyong Min ◽  
Hui Guo ◽  
Shengmei Luo

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