Real-time 3D hand shape estimation based on inverse kinematics and physical constraints

HANDLE Open Access

Abstract

We are researching for real-time hand shape estimation, which we are going to apply to user interface and interactive applications. We have employed a computer vision approach, since unwired sensing provides restriction-free observation, or a natural way of sensing. The problem is that since a human hand has many joints, it has geometrically high degrees of freedom, which makes hand shape estimation difficult. For example, we have to deal with a self-occlusion problem and a large amount of computation. At the same time, a human hand has several physical constraints, i.e., each joint has a movable range and interdependence, which can potentially reduce the search space of hand shape estimation. This paper proposes a novel method to estimate 3D hand shapes in real-time by using shape features acquired from camera images and physical hand constraints heuristically introduced. We have made preliminary experiments using multiple cameras under uncomplicated background. We show experimental results in order to verify the effectiveness of our proposed method.

Journal

Keywords

Details 詳細情報について

  • CRID
    1050017057726954240
  • NII Article ID
    120006655188
  • HANDLE
    2324/5910
  • Text Lang
    en
  • Article Type
    conference paper
  • Data Source
    • IRDB
    • CiNii Articles

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