DocumentCode :
384249
Title :
Tracking multiple animals in wildlife footage
Author :
Tweed, David ; Calway, Andrew
Author_Institution :
Dept. of Comput. Sci., Bristol Univ., UK
Volume :
2
fYear :
2002
fDate :
2002
Firstpage :
24
Abstract :
We describe a method for tracking animals in wildlife footage. It uses a CONDENSATION particle filtering frame-work driven by learnt characteristics of specific animals. The key contribution is a periodic model of animal motion based on the relative positions over time of trackable features at significant body points. We also introduce techniques for maintaining a multimodal state density within the particle filter over time to enable consistent tracking of multiple animals. Initial experiments show that the approach has considerable potential.
Keywords :
filtering theory; image motion analysis; image sequences; object detection; optical tracking; video signal processing; CONDENSATION particle filtering framework; animal characteristics; body points; multimodal state density; multiple animal tracking; periodic animal motion model; trackable features; video; wildlife footage; Animals; Computer science; Data mining; Focusing; Image sequences; Layout; Particle tracking; Probability distribution; Robustness; Wildlife;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2002. Proceedings. 16th International Conference on
ISSN :
1051-4651
Print_ISBN :
0-7695-1695-X
Type :
conf
DOI :
10.1109/ICPR.2002.1048227
Filename :
1048227
Link To Document :
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