A novel approach for recognition of human actions with semi-global features
In this study a new approach is presented for the recognition of human actions of everyday life with a fixed camera. The originality of the presented method consists in characterizing sequences by a temporal succession of semi-global features, which are extracted from “space-time micro-volumes”. The...
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| Veröffentlicht in: | Machine vision and applications 2008, Vol.19 (1), p.27-34 |
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| container_title | Machine vision and applications |
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| creator | Achard, Catherine Qu, Xingtai Mokhber, Arash Milgram, Maurice |
| description | In this study a new approach is presented for the recognition of human actions of everyday life with a fixed camera. The originality of the presented method consists in characterizing sequences by a temporal succession of semi-global features, which are extracted from “space-time micro-volumes”. The advantage of this approach lies in the use of robust features (estimated on several frames) associated with the ability to manage actions with variable durations and easily segment the sequences with algorithms that are specific to time-varying data. Each action is actually characterized by a temporal sequence that constitutes the input of a Hidden Markov Model system for the recognition. Results presented of 1,614 sequences performed by several persons validate the proposed approach. |
| doi_str_mv | 10.1007/s00138-007-0074-2 |
| format | Article |
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| ispartof | Machine vision and applications, 2008, Vol.19 (1), p.27-34 |
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| language | eng |
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| source | SpringerLink Journals - AutoHoldings |
| subjects | Artificial Intelligence Communications Engineering Computer Science Image Processing and Computer Vision Networks Original Paper Pattern Recognition |
| title | A novel approach for recognition of human actions with semi-global features |
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