@article{Zhengyu_Limin_Li_2015, title={Passenger Flow Detection of Video Surveillance: A Case Study of High-Speed Railway Transport Hub in China}, volume={21}, url={https://eejournal.ktu.lt/index.php/elt/article/view/9805}, DOI={10.5755/j01.eee.21.1.9805}, abstractNote={<p>Detect moving object from a video sequence is a fundamental and critical task in many computer vision applications. With video surveillance system of high-speed railway transport hub, one of the aims for passenger flow detection is to accurately and promptly detect potential safety hazard hidden in passenger flow. In this paper, a procedure of passenger flow detection in high-speed railway transport hub is presented. According to the key steps of procedure, a modified background model based on Dempster-Shafer theory, and a passenger flow status recognition algorithm based on features of image connected domain are proposed to improve the accuracy and real-time performance of passenger flow detection. Credit and effects of proposed methods were proved by experiment on data from high-speed railway transport hub video surveillance system.</p><p>DOI: <a href="http://dx.doi.org/10.5755/j01.eee.21.1.9805">http://dx.doi.org/10.5755/j01.eee.21.1.9805</a></p>}, number={1}, journal={Elektronika ir Elektrotechnika}, author={Zhengyu, Xie and Limin, Jia and Li, Wang}, year={2015}, month={Feb.}, pages={48-53} }