Detection and tracking of multiple humans in high-density crowds (Record no. 27878)

MARC details
000 -LEADER
fixed length control field 04046nas|a2200421 a 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20260818090354.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 091112s2009 th uu|m rtt 0| a1eng d
035 ## - SYSTEM CONTROL NUMBER
System control number .b1207035x
099 #9 - LOCAL FREE-TEXT CALL NUMBER (OCLC)
Classification number AIT RSPR no.CS-09-03
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Ali, Irshad
245 10 - TITLE STATEMENT
Title Detection and tracking of multiple humans in high-density crowds
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Pathum Thani, Thailand :
Name of publisher, distributor, etc. Asian Institute of Technology,
Date of publication, distribution, etc. 2009
300 ## - PHYSICAL DESCRIPTION
Extent 33 p. :
Other physical details ill.
490 1# - SERIES STATEMENT
Series statement Research studies project report ;
Volume/sequential designation no. CS-09-03
500 ## - GENERAL NOTE
General note Submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Computer Science, School of Engineering and Technology
502 ## - DISSERTATION NOTE
Dissertation note Research Studies Project Report (M.Eng.) - Asian Institute of Technology, 2009
520 ## - SUMMARY, ETC.
Summary, etc. 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. The visual surveillance system has become popular research area in computer vision. There are many algorithms exists to detect and track people in video stream. Human detection and tracking in high density crowds where object occlusion is very high is still an unsolved problem. Many preprocessing techniques such as background subtraction are fail in such situations. I present a fully automatic approach to multiple human detection and tracking in high density crowds in the presence of extreme occlusion. We integrate human detection and tracking into a single framework, and introduce a confirmation-by-classification method to estimate confidence in a tracked trajectory, track humans through occlusions, and eliminate false positive detections. I search for new humans in those parts of each frame where humans have not been detected previously. I increase and decrease the weight of tracks through confirmation-by-classification process. This is helpful to remove those tracks (false positives) which not confirmed for long time. I keep the tracks which have not been confirmed only for a short period of time, to give chance to those tracks where human are occluded fully or partially for a short period of time to rejoin their tracks. We use a Viola and Jones AdaBoost cascade classifier for detection, a particle filer for tracking, and color histograms for appearance modeling. An experimental evaluation shows that our approach is capable of tracking humans in high density crowds despite occlusions. On a test set with 35.35 humans per image achieves 76.8% hit rate with 2.05 false positives per image and 8.2 missed humans per image. The results form a strong basis for farthar research.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Signal detection
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Dailey, Matthew N.
Relator term Chairperson
700 0# - ADDED ENTRY--PERSONAL NAME
Personal name Manukid Parnichkun
Relator term Examination Committee
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Afzulpurkar, Nitin V.
Relator term Examination Committee
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element Higher Education Commission (HEC), Pakistan,
Relator term Scholarship Donor
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element Asian Institute of Technology Fellowship,
Relator term Scholarship Donor
810 2# - SERIES ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element Asian Institute of Technology.
Title of a work Research studies project report ;
Volume/sequential designation no. CS-09-03
856 ## - ELECTRONIC LOCATION AND ACCESS
Materials specified Full-Text
Uniform Resource Identifier <a href=" http://203.159.5.9/ait-thesis/detail.php?q=B11485"> http://203.159.5.9/ait-thesis/detail.php?q=B11485</a>
907 ## - LOCAL DATA ELEMENT G, LDG (RLIN)
a .b1207035x
b mnait
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902 ## - LOCAL DATA ELEMENT B, LDB (RLIN)
a 240329
998 ## - LOCAL CONTROL INFORMATION (RLIN)
Operator's initials, OID (RLIN) 0
Cataloger's initials, CIN (RLIN) 091112
First date, FD (RLIN) m
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-- u
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945 ## - LOCAL PROCESSING INFORMATION (OCLC)
l mnait
945 ## - LOCAL PROCESSING INFORMATION (OCLC)
l mnait
945 ## - LOCAL PROCESSING INFORMATION (OCLC)
l mnarc
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type 20-AIT Publication
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type 40-Archives
909 ## - LOCAL ITEMS USED
Barcode Barcode : 30050120615645
CREATED CREATED : 2009-12-11
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CREATED CREATED : 2016-03-31
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Holdings
Withdrawn status Lost status Damaged status Not for loan Home library Current library Shelving location Date acquired Cost, normal purchase price Total checkouts Full call number Barcode Date last seen Copy number Price effective from Koha item type
      Available for Loans Asian Institute of Technology Library Asian Institute of Technology Library AIT Publications 18/08/2026 50.00   AIT RSPR no.CS-09-03 30050120615645 18/08/2026 1 18/08/2026 20-AIT Publication
      Available for Loans Asian Institute of Technology Library Asian Institute of Technology Library AIT Publications 18/08/2026 50.00   AIT RSPR no.CS-09-03 30050120615637 18/08/2026 2 18/08/2026 20-AIT Publication
      Available for Loans Asian Institute of Technology Library Asian Institute of Technology Library Archives 18/08/2026     AIT RSPR no.CS-09-03 30050120239446 18/08/2026 1 18/08/2026 40-Archives
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