Capturing human hand motion in image sequences

J. Lin, Ying Wu, T. S. Huang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

41 Scopus citations


Visually capturing human hand motion requires estimating the 3D hand global pose as well as its local finger articulations. This is a challenging task that requires a search in a high dimensional space due to the high degrees of freedom that fingers exhibit and the self occlusions caused by global hand motion. We propose a divide and conquer approach to estimate both global and local hand motion. By looking into the palm and extra feature points provided by fingers, the hand pose is determined from the palm using an iterative closed point (ICP) algorithm and factorization method. The hand global pose serves as the base frame for the finger motion capturing. Noticing the natural hand motion constraints, we propose an efficient tracking algorithm based on a sequential Monte Carlo technique for tracking finger motion. To enhance the accuracy, pose estimations and finger articulation tracking are performed in an iterative manner. Our experiments show that our approach is accurate and robust for natural hand movements.

Original languageEnglish (US)
Title of host publicationProceedings - Workshop on Motion and Video Computing, MOTION 2002
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)0769518605, 9780769518602
StatePublished - 2002
EventWorkshop on Motion and Video Computing, MOTION 2002 - Orlando, United States
Duration: Dec 5 2002Dec 6 2002

Publication series

NameProceedings - Workshop on Motion and Video Computing, MOTION 2002


OtherWorkshop on Motion and Video Computing, MOTION 2002
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Media Technology


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