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.

引用

页码：72 / 84

页数：12

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