DocumentCode :
1164760
Title :
A noniterative greedy algorithm for multiframe point correspondence
Author :
Shafique, Khurram ; Shah, Mubarak
Author_Institution :
Sch. of Comput. Sci., Univ. of Central Florida, Orlando, FL, USA
Volume :
27
Issue :
1
fYear :
2005
Firstpage :
51
Lastpage :
65
Abstract :
This work presents a framework for finding point correspondences in monocular image sequences over multiple frames. The general problem of multiframe point correspondence is NP-hard for three or more frames. A polynomial time algorithm for a restriction of this problem is presented and is used as the basis of the proposed greedy algorithm for the general problem. The greedy nature of the proposed algorithm allows it to be used in real-time systems for tracking and surveillance, etc. In addition, the proposed algorithm deals with the problems of occlusion, missed detections, and false positives by using a single noniterative greedy optimization scheme and, hence, reduces the complexity of the overall algorithm as compared to most existing approaches where multiple heuristics are used for the same purpose. While most greedy algorithms for point tracking do not allow the entry and exit of the points from the scene, this is not a limitation for the proposed algorithm. Experiments with real and synthetic data over a wide range of scenarios and system parameters are presented to validate the claims about the performance of the proposed algorithm.
Keywords :
computational complexity; greedy algorithms; image sequences; optimisation; polynomials; real-time systems; tracking; NP-hard problems; monocular image sequences; multiframe point correspondence; multiple heuristics; noniterative greedy algorithm; occlusion; optimization; point tracking algorithm; polynomial time algorithm; real time systems; surveillance; Greedy algorithms; Humans; Image sequences; Layout; Motion analysis; Particle tracking; Polynomials; Real time systems; Surveillance; Target tracking; Index Terms- Point correspondence; bipartite graph matching; data association; motion; occlusion; path cover of directed graph.; point trajectory; target tracking; Algorithms; Artificial Intelligence; Computer Graphics; Computer Simulation; Image Enhancement; Image Interpretation, Computer-Assisted; Information Storage and Retrieval; Models, Biological; Models, Statistical; Movement; Numerical Analysis, Computer-Assisted; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Subtraction Technique; User-Computer Interface; Video Recording;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/TPAMI.2005.1
Filename :
1359751
Link To Document :
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