PROBABILISTIC HUMAN POSE RECOVERY FROM 2D IMAGES

被引：1
|
作者：
Flitti, F. [1 ]
Bennamoun, M. [1 ]
Huynh, D. Q. [1 ]
Owens, R. A. [1 ]
机构：
[1] Univ Western Australia, Sch Comp Sci & Software Engn, Nedlands, WA 6009, Australia
来源：
2010 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING | 2010年
关键词：
Human pose; silhouette; image moments; Gaussian Mixture Model; Neural Networks; RECOGNITION;
D O I：
10.1109/ICIP.2010.5652502
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Image based human pose recovery has many applications in different industries such as games, entertainment, physiological rehabilitation and biometrics. This paper presents a new pose estimation algorithm from monocular images based on a nonlinear mapping of human silhouettes, coded using a collection of local image moments, to the pose space using a mixture of Neural Networks (NN) regressors. All parameters are estimated automatically. Experiments and comparative results show a superior performance of the proposed method.
引用
收藏
页码：1517 / 1520
页数：4
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