DocumentCode :
431449
Title :
Hybrid Particle Filter and Mean Shift tracker with adaptive transition model
Author :
Maggio, Emilio ; Cavallaro, Andrea
Author_Institution :
Multimedia & Vision Lab., Queen Mary, Univ. of London, UK
Volume :
2
fYear :
2005
fDate :
March 18-23, 2005
Firstpage :
221
Lastpage :
224
Keywords :
adaptive estimation; adaptive filters; image sampling; probability; target tracking; tracking filters; video signal processing; adaptive state transition model; adaptive variances; hybrid particle filter; local maximum; mean shift tracker; multi-modal pdf; partial occlusions; position estimation; samples; target size estimation; total occlusions; Filtering algorithms; Histograms; Iterative algorithms; Kernel; Laboratories; Particle filters; Particle tracking; Predictive models; Robustness; Target tracking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2005. Proceedings. (ICASSP '05). IEEE International Conference on
ISSN :
1520-6149
Print_ISBN :
0-7803-8874-7
Type :
conf
DOI :
10.1109/ICASSP.2005.1415381
Filename :
1415381
Link To Document :
https://search.ricest.ac.ir/dl/search/defaultta.aspx?DTC=49&DC=431449
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