Selection of Characteristic Frames in Video for Efficient Action Recognition

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概要

• 論文の詳細を見る

• Vision based human action recognition has been an active research field in recent years. Exemplar matching is an important and popular methodology in this field, however, most previous works perform exemplar matching on the whole input video clip for recognition. Such a strategy is computationally expensive and limits its practical usage. In this paper, we present a martingale framework for selection of characteristic frames from an input video clip without requiring any prior knowledge. Action recognition is operated on these selected characteristic frames. Experiments on 10 studied actions from WEIZMANN dataset demonstrate a significant improvement in computational efficiency (54% reduction) while achieving the same recognition precision.

• The Institute of Electronics, Information and Communication Engineersの論文

著者

• TOYAMA Jun

  Laboratory of Pattern Recognition and Machine Learning, Graduate School of Information Science and Technology, Hokkaido university

• LU Guoliang

  Laboratory of Pattern Recognition and Machine Learning, Graduate School of Information Science and Technology, Hokkaido university

• KUDO Mineichi

  Laboratory of Pattern Recognition and Machine Learning, Graduate School of Information Science and Technology, Hokkaido university

関連論文

• Self-Similarities in Difference Images: A New Cue for Single-Person Oriented Action Recognition
• Selection of Characteristic Frames in Video for Efficient Action Recognition

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