| 한글제목(Korean Title) |
Silhouette-Edge-Based Descriptor for Human Action Representation and Recognition |
| 영문제목(English Title) |
Silhouette-Edge-Based Descriptor for Human Action Representation and Recognition |
| 저자(Author) |
Wilfred O. Odoyo
Jae-Ho Choi
In-Kyu Moon
Beom-Joon Cho
|
| 원문수록처(Citation) |
VOL 11 NO. 02 PP. 0124 ~ 0131 (2013. 06) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
Extraction and representation of postures and/or gestures from human activities in videos have been a focus of research in this area of action recognition. With various applications cropping up from different fields, this paper seeks to improve the performance of these action recognition machines by proposing a shape-based silhouette-edge descriptor for the human body. Information entropy, a method to measure the randomness of a sequence of symbols, is used to aid the selection of vital key postures from video frames. Morphological operations are applied to extract and stack edges to uniquely represent different actions shape-wise. To classify an action from a new input video, a Hausdorff distance measure is applied between the gallery representations and the query images formed from the proposed procedure. The method is tested on known public databases for its validation. An effective method of human action annotation and description has been effectively achieved. |
| 키워드(Keyword) |
Action recognition
Hausdorff distance
Shape descriptor
Silhouette-edge-based
|
| 파일첨부 |
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