Novel Kernel-Based Recognizers of Human Actions
<p/> <p>We study unsupervised and supervised recognition of human actions in video sequences. The videos are represented by probability distributions and then meaningfully compared in a probabilistic framework. We introduce two novel approaches outperforming state-of-the-art algorithms when tested o...
Збережено в:
| Автори: | , , |
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| Формат: | Artigo |
| Мова: | Inglês |
| Опубліковано: |
SpringerOpen
2010-01-01
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| Серія: | EURASIP Journal on Advances in Signal Processing |
| Онлайн доступ: | http://asp.eurasipjournals.com/content/2010/202768 |
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