Hand gesture recognition based on free-form contours and probabilistic inference

Włodzimierz Kasprzak; Artur Wilkowski; Karol Czapnik

International Journal of Applied Mathematics and Computer Science (2012)

  • Volume: 22, Issue: 2, page 437-448
  • ISSN: 1641-876X

Abstract

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A computer vision system is described that captures color image sequences, detects and recognizes static hand poses (i.e., "letters") and interprets pose sequences in terms of gestures (i.e., "words"). The hand object is detected with a double-active contour-based method. A tracking of the hand pose in a short sequence allows detecting "modified poses", like diacritic letters in national alphabets. The static hand pose set corresponds to hand signs of a thumb alphabet. Finally, by tracking hand poses in a longer image sequence, the pose sequence is interpreted in terms of gestures. Dynamic Bayesian models and their inference methods (particle filter and Viterbi search) are applied at this stage, allowing a bi-driven control of the entire system.

How to cite

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Włodzimierz Kasprzak, Artur Wilkowski, and Karol Czapnik. "Hand gesture recognition based on free-form contours and probabilistic inference." International Journal of Applied Mathematics and Computer Science 22.2 (2012): 437-448. <http://eudml.org/doc/208120>.

@article{WłodzimierzKasprzak2012,
abstract = {A computer vision system is described that captures color image sequences, detects and recognizes static hand poses (i.e., "letters") and interprets pose sequences in terms of gestures (i.e., "words"). The hand object is detected with a double-active contour-based method. A tracking of the hand pose in a short sequence allows detecting "modified poses", like diacritic letters in national alphabets. The static hand pose set corresponds to hand signs of a thumb alphabet. Finally, by tracking hand poses in a longer image sequence, the pose sequence is interpreted in terms of gestures. Dynamic Bayesian models and their inference methods (particle filter and Viterbi search) are applied at this stage, allowing a bi-driven control of the entire system.},
author = {Włodzimierz Kasprzak, Artur Wilkowski, Karol Czapnik},
journal = {International Journal of Applied Mathematics and Computer Science},
keywords = {active contours; hand pose detection; hand tracking; image sequence analysis; stochastic inference},
language = {eng},
number = {2},
pages = {437-448},
title = {Hand gesture recognition based on free-form contours and probabilistic inference},
url = {http://eudml.org/doc/208120},
volume = {22},
year = {2012},
}

TY - JOUR
AU - Włodzimierz Kasprzak
AU - Artur Wilkowski
AU - Karol Czapnik
TI - Hand gesture recognition based on free-form contours and probabilistic inference
JO - International Journal of Applied Mathematics and Computer Science
PY - 2012
VL - 22
IS - 2
SP - 437
EP - 448
AB - A computer vision system is described that captures color image sequences, detects and recognizes static hand poses (i.e., "letters") and interprets pose sequences in terms of gestures (i.e., "words"). The hand object is detected with a double-active contour-based method. A tracking of the hand pose in a short sequence allows detecting "modified poses", like diacritic letters in national alphabets. The static hand pose set corresponds to hand signs of a thumb alphabet. Finally, by tracking hand poses in a longer image sequence, the pose sequence is interpreted in terms of gestures. Dynamic Bayesian models and their inference methods (particle filter and Viterbi search) are applied at this stage, allowing a bi-driven control of the entire system.
LA - eng
KW - active contours; hand pose detection; hand tracking; image sequence analysis; stochastic inference
UR - http://eudml.org/doc/208120
ER -

References

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