Adaptive particle sampling and adaptive appearance for multiple video object tracking

NCU Institutional Repository > 資訊電機學院 > 資訊工程研究所 > 期刊論文 > Item 987654321/29098

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题名:	Adaptive particle sampling and adaptive appearance for multiple video object tracking
作者:	Cheng,HY;Hwang,JN
贡献者:	資訊工程研究所
关键词:	FILTERS;MODELS
日期:	2009
上传时间:	2010-06-29 20:13:41 (UTC+8)
出版者:	中央大學
摘要:	In this work, we propose an innovative method to integrate the Kalman filter and adaptive particle sampling for multiple video object tracking. Taking advantage of both the closed-form equations for optimal prediction and update from Kalman filters and the versatility of particle sampling for measurement selection under occlusion or segmentation error cases, the proposed method achieves both high tracking accuracy and computational simplicity. The adaptive particle sampling, which uses parameters updated by Kalman filters, can thus require only a small number of particles to achieve high positioning and scaling accuracy. Also, the concept of adaptive appearance is applied to enhance the robustness of occlusion handling. The experimental results confirm the effectiveness of the proposed method. (C) 2009 Elsevier B.V. All rights reserved.
關聯:	SIGNAL PROCESSING
显示于类别:	[資訊工程研究所] 期刊論文

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