DocumentCode :
453920
Title :
Robust Multi-Object Tracking Under a Wide Range of Real-World Conditions
Author :
Al-Hamadi, Ayoub K. ; Michaelis, Bernd
Author_Institution :
Inst. for Electron., Signal Process. & Commun., Otto-von-Guericke-Univ. Magdeburg
Volume :
1
fYear :
2005
fDate :
28-30 Nov. 2005
Firstpage :
815
Lastpage :
820
Abstract :
In this paper we propose a new paradigm for solving the correspondence problem and then determination of a motion trajectory based on a trisectional structure. The paradigm distinguishes between real world objects; extracts image features such as motion blobs and color patches; and abstract objects such as meta objects that denote real-world physical objects. The efficiency of the proposed method for determining the motion trajectories of moving objects are demonstrated in this paper on the basis of the analysis of real image sequences that are subject to severe disturbances (e.g. congestion and lighting transitions)
Keywords :
feature extraction; image colour analysis; image motion analysis; image sequences; object detection; target tracking; color structure code algorithm; feature extraction; motion blob; motion trajectory; real image sequence; real-world physical object; robust multiobject tracking; trisectional structure; Feature extraction; Image motion analysis; Image sequences; Merging; Motion analysis; Object detection; Robustness; Tracking; Trajectory; Video sequences;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence for Modelling, Control and Automation, 2005 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, International Conference on
Conference_Location :
Vienna
Print_ISBN :
0-7695-2504-0
Type :
conf
DOI :
10.1109/CIMCA.2005.1631365
Filename :
1631365
Link To Document :
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