Active classification for human action recognition
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Yksityiskohdat
| Alkuperäiskieli | Englanti |
|---|---|
| Otsikko | 2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings |
| Sivut | 3249-3253 |
| Sivumäärä | 5 |
| DOI - pysyväislinkit | |
| Tila | Julkaistu - 2013 |
| OKM-julkaisutyyppi | A4 Artikkeli konferenssijulkaisussa |
| Tapahtuma | 2013 20th IEEE International Conference on Image Processing, ICIP 2013 - Melbourne, VIC, Austraalia Kesto: 15 syyskuuta 2013 → 18 syyskuuta 2013 |
Conference
| Conference | 2013 20th IEEE International Conference on Image Processing, ICIP 2013 |
|---|---|
| Maa | Austraalia |
| Kaupunki | Melbourne, VIC |
| Ajanjakso | 15/09/13 → 18/09/13 |
Tiivistelmä
In this paper, we propose a novel classification method involving two processing steps. Given a test sample, the training data residing to its neighborhood are determined. Classification is performed by a Single-hidden Layer Feedforward Neural network exploiting labeling information of the training data appearing in the test sample neighborhood and using the rest training data as unlabeled. By following this approach, the proposed classification method focuses the classification problem on the training data that are more similar to the test sample under consideration and exploits information concerning to the training set structure. Compared to both static classification exploiting all the available training data and dynamic classification involving data selection for classification, the proposed active classification method provides enhanced classification performance in two publicly available action recognition databases.