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Estimation of 3-D human body posture via co-registration of 3-D human model and sequential stereo information

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Abstract

In this paper, we present a technique for estimating three-dimensional (3-D) human body posture from a set of sequential stereo images. We estimated the pixel displacements of stereo image pairs to reconstruct 3-D information. We modeled the human body with a set of ellipsoids connected by kinematic chains and parameterized with rotational angles at each body joint. To estimate human posture from the 3-D data, we developed a new algorithm based on expectation maximization (EM) with two-step iterations, assigning the 3-D data to different body parts and refining the kinematic parameters to fit the 3-D model to the data. The algorithm is iterated until it converges on the correct posture. Experimental results with synthetic and real data demonstrate that our method is capable of reconstructing 3-D human posture from stereo images. Our method is robust and generic; any useful information for locating the body parts can be integrated into our framework to improve the outcomes.

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Authors and Affiliations

  1. Department of Computer Engineering, Kyung Hee University, Seocheon-dong, Giheung-gu, Yongin-si, Gyeonggi-do, 446-701, South Korea

    Nguyen Duc Thang, Young-Koo Lee & Sungyoung Lee

  2. Department of Biomedical Engineering, Kyung Hee University, Seocheon-dong, Giheung-gu, Yongin-si, Gyeonggi-do, 446-701, South Korea

    Tae-Seong Kim

Authors
  1. Nguyen Duc Thang
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  2. Tae-Seong Kim
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  3. Young-Koo Lee
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  4. Sungyoung Lee
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Correspondence to Tae-Seong Kim.

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Thang, N.D., Kim, TS., Lee, YK. et al. Estimation of 3-D human body posture via co-registration of 3-D human model and sequential stereo information. Appl Intell 35, 163–177 (2011). https://doi.org/10.1007/s10489-009-0209-4

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  • DOI: https://doi.org/10.1007/s10489-009-0209-4

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