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| Titel: |
Human action categorization using discriminative local spatio-temporal feature weighting |
| Auteur: |
Ghodrati, Amir Kasaei, Shohreh |
| Verschenen in: |
Intelligent data analysis |
| Paginering: | Jaargang 16 (2012) nr. 4 pagina's 537-550 |
| Jaar: |
2012-07-19 |
| Inhoud: |
New methods based on local spatio-temporal features have exhibited significant performance in action recognition. In these methods, feature selection plays an important role to achieve a superior performance. Actions are represented by local spatio-temporal features extracted from action videos. Action representations are then classified by applying a classifier (such as k-nearest neighbor or SVM). In this paper, we have proposed two feature weighting methods to better discriminate similar actions. We have proposed a definition of feature discrimination power to be used in the feature selection process. Our proposed weighting schemes have greatly improved the final categorization accuracy on the well-known KTH and Weizmann datasets. |
| Uitgever: |
IOS Press |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
Details van artikel 6 van 11 gevonden artikelen
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