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Machine Vision and Applications

, Volume 26, Issue 7–8, pp 919–932 | Cite as

Human body motion parameters capturing using kinect

  • Shih-Chung Hsu
  • Jun-Yang Huang
  • Wei-Chia Kao
  • Chung-Lin HuangEmail author
Original Paper

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.

Keywords

Motion parameter estimation Random forest (RF) classifier Action type classifier Body part (BP) classifier Offset compensation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Shih-Chung Hsu
    • 1
  • Jun-Yang Huang
    • 1
  • Wei-Chia Kao
    • 1
  • Chung-Lin Huang
    • 2
    Email author
  1. 1.Department of Electrical EngineeringNational Tsing-Hua UniversityHsin-ChuTaiwan
  2. 2.Department of Applied Informatics and MultimediaAsia UniversityTai-ChungTaiwan

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