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Human body motion parameters capturing using kinect

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Abstract

This paper introduces a new real-time human motion parameters capturing method using Kinect. It consists of five modules. First, the hybrid action type classifier categories human body motion into four different action types. Second, for each action type, there is a body part (BP) classifier which segments the human silhouette into 16 BP regions of which the centroids become the BP joints. These BP joints are linked to represent the human body skeleton. Third, an action type validation process verifies the identified action type. Fourth, the partial occlusion recovery method relocates the occluded BP joints. Fifth, the offset compensation process fine tunes the positions of BP joints and then validates the compensation results. The major contributions of this paper are hybrid action type classification and correction, offset compensation, and partial occlusion recovery. The experimental results show that this method can estimate human upper limb motion parameters in real time accurately and effectively.

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Authors and Affiliations

  1. Department of Electrical Engineering, National Tsing-Hua University, Hsin-Chu, Taiwan

    Shih-Chung Hsu, Jun-Yang Huang & Wei-Chia Kao

  2. Department of Applied Informatics and Multimedia, Asia University, Tai-Chung, Taiwan

    Chung-Lin Huang

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  1. Shih-Chung Hsu
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  2. Jun-Yang Huang
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  3. Wei-Chia Kao
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Correspondence to Chung-Lin Huang.

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Hsu, SC., Huang, JY., Kao, WC. et al. Human body motion parameters capturing using kinect. Machine Vision and Applications 26, 919–932 (2015). https://doi.org/10.1007/s00138-015-0710-1

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