Gesture recognition using sparse code of hierarchical SOM

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

25 Citations (Scopus)


We propose an approach to recognize time-series gesture patterns with Hierarchical Self-Organizing Map(HSOM). One of the key issue of the time-series pattern recognition is to absorb the time variant appropriately and to make cluters which include the same gesture class. In our approach. we arrange the SOM hierarchically. In each layer ofthe SOM time series patterns divided into some periods; postures, gesture elements and gestures. They are learned in each layer of HSOM. For example, postures are learned in the first layer, gesture elements are learned in the second layer and so on. Using the sparse code in the bottom layer, the SOM can perform time invarient recognition of the gesture elements and gestures.

Original languageEnglish
Title of host publication2008 19th International Conference on Pattern Recognition, ICPR 2008
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781424421756
Publication statusPublished - 2008

Publication series

NameProceedings - International Conference on Pattern Recognition
ISSN (Print)1051-4651

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition


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