Regression-Aware Classification Feature for Pedestrian Detection and Tracking in Video Surveillance Systems

Author(s):  
Xuan-Thuy Vo ◽  
Tien-Dat Tran ◽  
Duy-Linh Nguyen ◽  
Kang-Hyun Jo
2017 ◽  
Vol 27 (10) ◽  
pp. 2260-2273 ◽  
Author(s):  
Muhammad Bilal ◽  
Asim Khan ◽  
Muhammad Umar Karim Khan ◽  
Chong-Min Kyung

2012 ◽  
Vol 17 (4) ◽  
pp. 283-295
Author(s):  
Mateusz Komorkiewicz ◽  
Jaromir Przybyło

Abstract Because the amount of various video streams recorded by video surveillance systems is increasing, the new approach, where human operator analyzing the video is replaced by artificial intelligence system is gaining new followers. The algorithm have to meet several requirements: must be accurate and not produce too many false alarms, moreover it must be able to process the received video stream in real-time to provide sufficient response time. In the article a system is presented which is able to detect and analyze walking pedestrians. It is based on two algorithms: scale space and matching contours using distance transform. The information can be used by other parts of the advanced video surveillance system, namely object tracking by detection, detecting heavy equipment only zone intrusion or for sorting out possible suspicious persons (pickpocket, homeless etc.).


2018 ◽  
Vol 7 (2.31) ◽  
pp. 117
Author(s):  
Mohammed Abdulraheem Fadhel ◽  
Omran Al-Shamaa ◽  
Bahaa Husain Taher

With the growth of the electronic and communication devices, computer vision has become an significant application of smart cities. A smart city is controlled by smart autonomous systems. Many algorithms have been developed to satisfy these smart cities. This paper concerned with addressing the moving objects (vehicles) by using morphological techniques. For computational cheapness. The simulation has been built by a MATLAB 2012a and its implementation was done using Xilinx-ISE 14.6 (2013) XC3S700A-FPGA board that provides an exceptional tool for mixing between two platforms, the ISE 14.6(2013) and the MATLAB (2012a) platforms. MATLAB provides components for FPGA that invoke Verilog code of Xilinx platform, to avoid the size weakness of XC3S700A-FPGA board. 


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