Real-Time Body Pose Recognition Using 2D or 3D Haarlets

被引：0
|
作者：
Michael Van den Bergh
Esther Koller-Meier
Luc Van Gool
机构：
[1] ETH Zurich,Computer Vision Laboratory
[2] Katholieke Universiteit Leuven,ESAT
来源：
International Journal of Computer Vision | 2009年 / 83卷
关键词：
Pose estimation; Pose recognition; Silhouettes; 3D hulls; LDA; ANMM; Haarlets;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This article presents a novel approach to markerless real-time pose recognition in a multicamera setup. Body pose is retrieved using example-based classification based on Haar wavelet-like features to allow for real-time pose recognition. Average Neighborhood Margin Maximization (ANMM) is introduced as a powerful new technique to train Haar-like features. The rotation invariant approach is implemented for both 2D classification based on silhouettes, and 3D classification based on visual hulls.
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页码：72 / 84
页数：12
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