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Tracking a Hand Manipulating an Object

Henning Hamer, Konrad Schindler, Esther Koller-Meier, Luc Van Gool
IEEE International Conference on Computer Vision (ICCV
October 2009


We present a method for tracking a hand while it is interacting with an object. This setting is arguably the one where hand-tracking has most practical relevance, but poses significant additional challenges: strong occlusions by the object as well as self-occlusions are the norm, and classical anatomical constraints need to be softened due to the external forces between hand and object. To achieve robustness to partial occlusions, we use an individual local tracker for each segment of the articulated structure. The segments are connected in a pairwise Markov random field, which enforces the anatomical hand structure through soft constraints on the joints between adjacent segments. The most likely hand configuration is found with belief propagation. Both range and color data are used as input. Experiments are presented for synthetic data with ground truth and for real data of people manipulating objects.

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  author = {Henning Hamer and Konrad Schindler and Esther Koller-Meier and Luc Van Gool},
  title = {Tracking a Hand Manipulating an Object},
  booktitle = {IEEE International Conference on Computer Vision (ICCV},
  year = {2009},
  month = {October},
  pages = {1475-1482},
  keywords = {}