@inproceedings{387a06cf0c8f445eb8a6289d99908fd2,
title = "High level feature: Head and body co-trakcing by Kalman filter",
abstract = "Tracking multiple targets in complex situation is challenging. The difficulties are tackled multiple targets with occlusions, especially when multiple involved targets are grouped and moving together in appearance. In this paper, we present a multiple targets tracking system for the management of occlusion problem. The proposed algorithm introduces a geometric shape co-tracking strategy. It decomposes targets into geometric shapes located on body and head parts based on reasonable target geometry consideration. Features selected from the decomposed geometric shapes then can be used to track targets through intersections such as occlusion. Projection histogram and ellipsoid shape model are adopted to manage decomposed geometric shapes corresponding to each target. Tracking is done through Kalman filtering process with high efficient and low complexity issue. Experimental results show that the occlusion of grouped targets can be tracked successfully on recent challenging benchmark sequences.",
keywords = "Correspondence, Feature extraction, Kalman filter, Morphological, Shape, Tracking",
author = "Chen, {Chun Hua} and Lin, {Chung Yuan} and Li, {Sz Yan} and Tsai, {Tsung Han}",
year = "2010",
doi = "10.1109/ICIP.2010.5651983",
language = "???core.languages.en_GB???",
isbn = "9781424479948",
series = "Proceedings - International Conference on Image Processing, ICIP",
pages = "725--728",
booktitle = "2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings",
note = "2010 17th IEEE International Conference on Image Processing, ICIP 2010 ; Conference date: 26-09-2010 Through 29-09-2010",
}