Gesture recognition using HLAC features of PARCOR images and HMM based recognizer

Takio Kurita, Satoru Hayamizu

研究成果: Conference contribution

25 被引用数 (Scopus)

抄録

The paper proposes a gesture recognition method which uses higher order local autocorrelation (HLAC) features extracted from PARCOR images. To extract dominant information from a sequence of images, the authors apply a linear prediction coding technique to the sequence of pixel values and PARCOR images are constructed from the PARCOR coefficients of the sequences of the pixel values. From the PARCOR images, HLAC features are extracted and the sequences of the features are used as the input vectors of the hidden Markov model (HMM) based recognizer. Since HLAC features are inherently shift-invariant and computationally inexpensive, the proposed method becomes robust to changes of shift of the person's position and makes real-time gesture recognition possible. Experimental results of gesture recognition are shown to evaluate the performance of the proposed method.

本文言語English
ホスト出版物のタイトルProceedings - 3rd IEEE International Conference on Automatic Face and Gesture Recognition, FG 1998
出版社IEEE Computer Society
ページ422-427
ページ数6
ISBN(印刷版)0818683449, 9780818683442
DOI
出版ステータスPublished - 1998
外部発表はい
イベント3rd IEEE International Conference on Automatic Face and Gesture Recognition, FG 1998 - Nara, Japan
継続期間: 1998 4 141998 4 16

出版物シリーズ

名前Proceedings - 3rd IEEE International Conference on Automatic Face and Gesture Recognition, FG 1998

Conference

Conference3rd IEEE International Conference on Automatic Face and Gesture Recognition, FG 1998
国/地域Japan
CityNara
Period98/4/1498/4/16

ASJC Scopus subject areas

  • コンピュータ ビジョンおよびパターン認識

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