Understanding presumption system from an image sequence using HMM

Teppei Inomata, Masafumi Hagiwara

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

Abstract

In this paper, the understanding presumption system from the gesture recognition using Hidden Markov Model (HMM) is proposed. The features of this system are 1) not limiting the gesture recognized, and 2) automatically extracting the feature points by using HMM without a user's hand. In particular, the time-line pictures of subject's face are r st input into the system. Then, the motion of their face region, pupils, and eyebrows are extracted as a feature vector from each still picture. Next, to the feature vector sequence is changed into the symbol sequence, gesture has been recognized by estimating likelihood of HMM which learned gesture beforehand, using Viterbi algorithm. At the end, their degree-of-comprehension is presumed from the appearance probability of the recognized gesture according to their understanding. At the time, we take a video of their solving a problem during the evaluation experiment. And their degree-of-comprehension are presumed for their picture as an input of a system. Consequently, it is shown that understanding presumption by the proposed method is possible.

Original languageEnglish
Title of host publicationConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Pages314-320
Number of pages7
Volume1
Publication statusPublished - 2004
Event2004 IEEE International Conference on Systems, Man and Cybernetics, SMC 2004 - The Hague, Netherlands
Duration: 2004 Oct 102004 Oct 13

Other

Other2004 IEEE International Conference on Systems, Man and Cybernetics, SMC 2004
CountryNetherlands
CityThe Hague
Period04/10/1004/10/13

Fingerprint

Hidden Markov models
Viterbi algorithm
Gesture recognition
Experiments

Keywords

  • Gesture recognition
  • HMM
  • Understanding presumption

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Inomata, T., & Hagiwara, M. (2004). Understanding presumption system from an image sequence using HMM. In Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics (Vol. 1, pp. 314-320)

Understanding presumption system from an image sequence using HMM. / Inomata, Teppei; Hagiwara, Masafumi.

Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics. Vol. 1 2004. p. 314-320.

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

Inomata, T & Hagiwara, M 2004, Understanding presumption system from an image sequence using HMM. in Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics. vol. 1, pp. 314-320, 2004 IEEE International Conference on Systems, Man and Cybernetics, SMC 2004, The Hague, Netherlands, 04/10/10.
Inomata T, Hagiwara M. Understanding presumption system from an image sequence using HMM. In Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics. Vol. 1. 2004. p. 314-320
Inomata, Teppei ; Hagiwara, Masafumi. / Understanding presumption system from an image sequence using HMM. Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics. Vol. 1 2004. pp. 314-320
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