Pose sentences: a new representation for action recognition using sequence of pose words

Date
2008-12
Advisor
Instructor
Source Title
19th International Conference on Pattern Recognition, 2008
Print ISSN
Electronic ISSN
Publisher
IEEE
Volume
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Pages
Language
English
Type
Conference Paper
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Journal ISSN
Volume Title
Abstract

We propose a method for recognizing human actions in videos. Inspired from the recent bag-of-words approaches, we represent actions as documents consisting of words, where a word refers to the pose in a frame. Histogram of oriented gradients (HOG) features are used to describe poses, which are then vector quantized to obtain pose-words. As an alternative to bagof- words approaches, that only represent actions as a collection of words by discarding the temporal characteristics of actions, we represent videos as ordered sequence of pose-words, that is as pose sentences. Then, string matching techniques are exploited to find the similarity of two action sequences. In the experiments, performed on data set of Blank et al., 92% performance is obtained. © 2008 IEEE.

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Keywords
A-frames, Action recognition, Action sequences, Bag of words, Data sets, Human actions, String matching, Temporal characteristics, Image recognition
Citation
Published Version (Please cite this version)