Human tracking with statistical shape model and rough pose estimation by random forest

Kiyoshi Hashimoto, Hirokatsu Kataoka, Yuji Sato, Masamoto Tanabiki, Yoshimitsu Aoki

研究成果: Article査読

抄録

Human tracking in surveillance camera has been challenging task in the field of computer vision. Tracking objects have large variations such as pose, body shape, clothes and so on. Especially in parts-based methods, postural change is big problem since appearnce of human changes drastically. We deal with this problem to use statistical shape model for tracking and detection. It represents the variations of postural change and body shape with low dimensions. Our trakcing result includes more detailed the position and shape of body pails. So we recognize rough pose and body direction to analyze it. These data is useful for seculity system or marketing decision in surveillance.

本文言語English
ページ(範囲)1162-1167
ページ数6
ジャーナルSeimitsu Kogaku Kaishi/Journal of the Japan Society for Precision Engineering
81
12
DOI
出版ステータスPublished - 2015

ASJC Scopus subject areas

  • 機械工学

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