Constraint-Based Optimized Human Skeleton Extraction from Single-Depth Camera

In: Sensors (June 2019), 19(11)(2604)
 

Abstract

As a cutting-edge research topic in computer vision and graphics for decades, human skeleton extraction from single-depth camera remains challenging due to possibly occurring occlusions of different body parts, huge appearance variations, and sensor noise. In this paper, we propose to incorporate human skeleton length conservation and symmetry priors as well as temporal constraints to enhance the consistency and continuity for the estimated skeleton of a moving human body. Given an initial estimation of the skeleton joint positions provided per frame by the Kinect SDK or Nuitrack SDK, which do not follow the aforementioned priors and can prone to errors, our framework improves the accuracy of these pose estimates based on the length and symmetry constraints. In addition, our method is device-independent and can be integrated into skeleton extraction SDKs for refinement, allowing the detection of outliers within the initial joint location estimates and predicting new joint location estimates following the temporal observations. The experimental results demonstrate the effectiveness and robustness of our approach in several cases.

Keywords: consistency, continuity, human skeleton extraction, skeleton constraints

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Bibtex

@ARTICLE{li2019sensors,
    author = {Li, Ruotong and Si, Weixin and Weinmann, Michael and Klein, Reinhard},
     pages = {2604},
     title = {Constraint-Based Optimized Human Skeleton Extraction from Single-Depth Camera},
   journal = {Sensors},
    volume = {19(11)},
      year = {2019},
     month = jun,
  keywords = {consistency, continuity, human skeleton extraction, skeleton constraints},
  abstract = {As a cutting-edge research topic in computer vision and graphics for decades, human skeleton
              extraction from single-depth camera remains challenging due to possibly occurring occlusions of
              different body parts, huge appearance variations, and sensor noise. In this paper, we propose to
              incorporate human skeleton length conservation and symmetry priors as well as temporal constraints
              to enhance the consistency and continuity for the estimated skeleton of a moving human body. Given
              an initial estimation of the skeleton joint positions provided per frame by the Kinect SDK or
              Nuitrack SDK, which do not follow the aforementioned priors and can prone to errors, our framework
              improves the accuracy of these pose estimates based on the length and symmetry constraints. In
              addition, our method is device-independent and can be integrated into skeleton extraction SDKs for
              refinement, allowing the detection of outliers within the initial joint location estimates and
              predicting new joint location estimates following the temporal observations. The experimental
              results demonstrate the effectiveness and robustness of our approach in several cases.},
       url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6603546/#},
       doi = {10.3390/s19112604}
}