Probabilistic pedestrian tracking based on a skeleton model

Jumpei Ashida, Ryusuke Miyamoto, Hiroshi Tsutsui, Takao Onoye, Yukihiro Nakamura

研究成果: Conference contribution

5 引用 (Scopus)

抜粋

A novel pedestrian tracking scheme based on a particle filter is proposed, which adopts a skeleton model of a pedestrian as a state space model and uses distance transformed images for likelihood estimation. The six-stick skeleton model used in the proposed approach is very distinctive in representing a pedestrian simply but effectively, with which the efficient state space for the pedestrian tracking can be derived. Experimental results by using PETS sample sequences demonstrate that the proposed approach achieves highly accurate pedestrian tracking without any of prior learning.

元の言語English
ホスト出版物のタイトル2006 IEEE International Conference on Image Processing, ICIP 2006 - Proceedings
ページ2825-2828
ページ数4
DOI
出版物ステータスPublished - 1 12 2006
イベント2006 IEEE International Conference on Image Processing, ICIP 2006 - Atlanta, GA, United States
継続期間: 8 10 200611 10 2006

出版物シリーズ

名前Proceedings - International Conference on Image Processing, ICIP
ISSN(印刷物)1522-4880

Conference

Conference2006 IEEE International Conference on Image Processing, ICIP 2006
United States
Atlanta, GA
期間8/10/0611/10/06

これを引用

Ashida, J., Miyamoto, R., Tsutsui, H., Onoye, T., & Nakamura, Y. (2006). Probabilistic pedestrian tracking based on a skeleton model. : 2006 IEEE International Conference on Image Processing, ICIP 2006 - Proceedings (pp. 2825-2828). [4107157] (Proceedings - International Conference on Image Processing, ICIP). https://doi.org/10.1109/ICIP.2006.312996