Constraining dense hand surface tracking with elasticity

By Breannan Smith, Chenglei Wu, He Wen, Patrick Peluse, Yaser Sheikh, Jessica K. Hodgins, Takaaki Shiratori. 2020

77 citations recorded by the source corpus.

Many of the actions that we take with our hands involve self-contact and occlusion: shaking hands, making a fist, or interlacing our fingers while thinking. This use of of our hands illustrates the importance of tracking hands through self-contact and occlusion for many applications in computer vision and graphics, but existing methods for tracking hands and faces are not designed to treat the extreme amounts of self-contact and self-occlusion exhibited by common hand gestures. By extending recent advances in vision-based tracking and physically based animation, we present the first algorithm capable of tracking high-fidelity hand deformations through highly self-contacting and self-occluding hand gestures, for both single hands and two hands. By constraining a vision-based tracking algorithm with a physically based deformable model, we obtain an algorithm that is robust to the ubiquitous self-interactions and massive self-occlusions exhibited by common hand gestures, allowing us to track two hand interactions and some of the most difficult possible configurations of a human hand.

Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition, Human-Computer Interaction

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In Aerospace Engineering

  1. Cheston Tan
  2. Jiafei Duan
  3. Samson Yu
  4. Tangyao Li
  5. Huaiyu Zhu

In Computer Vision and Pattern Recognition

  1. Jiafei Duan
  2. Samson Yu
  3. Cheston Tan
  4. Tangyao Li
  5. Huaiyu Zhu

Citations in the corpus