DocumentCode
424072
Title
An improved data assignment solution for ML-based relaxation approach for multitarget tracking problem
Author
Chen, Lung ; Hua, Qiang ; Li, Iao-Hong
Author_Institution
Dept. of Comput. Sci., Northern British Columbia Univ., Vancouver, BC, Canada
Volume
3
fYear
2004
fDate
26-29 Aug. 2004
Firstpage
1361
Abstract
It is proved that the optimal solution for the matching problem in multi-target tracking can be found from among n different matching. We show in this paper by simulation that the costs of the n different possible solutions constitute a bimodal sequence, which suggests an algorithm of O(N logN) complexity, lower than most of known algorithms.
Keywords
computational complexity; maximum likelihood sequence estimation; pattern matching; relaxation theory; target tracking; O(N logN) complexity algorithm; bimodal sequence; data assignment solution; maximum likelihood based relaxation method; multitarget tracking problem; pattern matching problem; Application software; Computer science; Costs; Information processing; Lungs; Machine learning; Mathematics; Sensor arrays; Surveillance; Target tracking;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN
0-7803-8403-2
Type
conf
DOI
10.1109/ICMLC.2004.1381985
Filename
1381985
Link To Document