04385nas|a2200517 a 4500 20260818090355.0 170313s2013 th uu|m rtt 0| a1eng d .b12180440 AIT Diss. no.CS-13-02 Ali, Irshad Detection and tracking of multiple humans in high-density crowds Pathum Thani, Thailand : Asian Institute of Technology, 2013 68 p. : ill. Dissertation ; no. CS-13-02 A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer Science, School of Engineering and Technology Thesis (Ph.D.) - Asian Institute of Technology, 2013 As public concern about crime and terrorist activity increases, the importance of public security is growing, and video surveillance systems are increasingly widespread tools for monitoring, management, and law enforcement in public areas. At the same time, video surveillance systems have become a popular research area in computer vision. Many algorithms exist to detect and track people in video streams. However, human detection and tracking in high density crowds, where object occlusion is very high, is still an unsolved problem. Pre-processing techniques such as background subtraction fail in such situations. The emphasis in this work is on the development of a fully automatic algorithm to detect and track multiple humans in high-density crowds in the presence of extreme occlusion. Typical approaches such as background modeling and body part-based pedestrian detection fail when most of the scene is in motion and most body parts of most of the pedestrians are occluded. Under these conditions, we believe that the head is the only body part that can be robustly detected and tracked. In this dissertation, we therefore present a method for tracking pedestrians that detects and tracks heads rather than full bodies. First, we use a Viola and Jones AdaBoost detection cascade to detect human heads in images. However, we do not rely particularly on the Viola and Jones method. Our method will improve upon the raw results of any head detector using a blend of detection, appearance-based tracking, and incremental head plane estimation. Any effective head detector could be plugged into our algorithm if it is capable of detecting heads in crowds. Electronic surveillance Computer vision Signal detection Dailey, Mathew N., Chairperson Afzulpurkar, Nitin V., Examination Committee Duboz, Raphael, Examination Committee Orwell, James, Examination committee Higher Education Commission (HEC), Pakistan, Scholarship donor Asian Institute of Technology Fellowship, Scholarship donor Asian Institute of Technology. Dissertation ; no. CS-13-02 Full-Text http://203.159.5.9/ait-thesis/detail.php?q=B00295 .b12180440 mnait m 240411 0 170313 m a m 0 000:001:PDF:b1218044:003023:0:0:0:0:0:0 Abstract--AIT Diss. no.CS-13-02 n mnait mnait mnarc mnarc mnarc 20 40 Barcode : 30050120407712 CREATED : 2017-03-13 RECORD # : i13069627 LPATRON : 0 LCHKIN : - # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 0 TOT RENEW : 0 Barcode : 30050120407688 CREATED : 2017-03-13 RECORD # : i13069639 LPATRON : 1015151 LCHKIN : 2019-02-04 # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 1 TOT RENEW : 4 Barcode : 30050120405914 CREATED : 2017-05-04 RECORD # : i13073734 LPATRON : 0 LCHKIN : - # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 0 TOT RENEW : 0 Barcode : 30050120978134 CREATED : 2020-09-18 RECORD # : i13297302 LPATRON : 0 LCHKIN : - # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 0 TOT RENEW : 0 Barcode : 30050120978126 CREATED : 2020-09-18 RECORD # : i13297314 LPATRON : 0 LCHKIN : - # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 0 TOT RENEW : 0 27879 27879 0 0 0 0 MAIN MAIN mnait 2026-08-18 50.00 0 AIT Diss. no.CS-13-02 30050120407712 2026-08-18 09:03:55 1 2026-08-18 20 0 0 0 0 MAIN MAIN mnait 2026-08-18 50.00 0 AIT Diss. no.CS-13-02 30050120407688 2026-08-18 09:03:55 2 2026-08-18 20 0 0 0 0 MAIN MAIN mnarc 2026-08-18 50.00 0 AIT Diss. no.CS-13-02 30050120405914 2026-08-18 09:03:55 1 2026-08-18 40 0 0 0 0 MAIN MAIN mnarc 2026-08-18 50.00 0 AIT Diss. no.CS-13-02 30050120978134 2026-08-18 09:03:55 3 2026-08-18 20 0 0 0 0 MAIN MAIN mnarc 2026-08-18 50.00 0 AIT Diss. no.CS-13-02 30050120978126 2026-08-18 09:03:55 4 2026-08-18 20