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

页码：1517 / 1520

页数：4

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