Variations of a Hough-Voting Action Recognition System
This paper presents two variations of a Hough-voting framework used for action recognition and shows classification results for low-resolution video and videos depicting human interactions. For low-resolution videos, where people performing actions are around 30 pixels, we adopt low-level features s...
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| Published in | Recognizing Patterns in Signals, Speech, Images and Videos pp. 306 - 312 |
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| Main Authors | , , , |
| Format | Book Chapter |
| Language | English Japanese |
| Published |
Berlin, Heidelberg
Springer Berlin Heidelberg
2010
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| Series | Lecture Notes in Computer Science |
| Subjects | |
| Online Access | Get full text |
| ISBN | 9783642177101 3642177107 |
| ISSN | 0302-9743 1611-3349 |
| DOI | 10.1007/978-3-642-17711-8_31 |
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| Abstract | This paper presents two variations of a Hough-voting framework used for action recognition and shows classification results for low-resolution video and videos depicting human interactions. For low-resolution videos, where people performing actions are around 30 pixels, we adopt low-level features such as gradients and optical flow. For group actions with human-human interactions, we take the probabilistic action labels from the Hough-voting framework for single individuals and combine them into group actions using decision profiles and classifier combination. |
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| AbstractList | This paper presents two variations of a Hough-voting framework used for action recognition and shows classification results for low-resolution video and videos depicting human interactions. For low-resolution videos, where people performing actions are around 30 pixels, we adopt low-level features such as gradients and optical flow. For group actions with human-human interactions, we take the probabilistic action labels from the Hough-voting framework for single individuals and combine them into group actions using decision profiles and classifier combination. |
| Author | Van Gool, Luc Waltisberg, Daniel Gall, Juergen Yao, Angela |
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| Copyright | Springer-Verlag Berlin Heidelberg 2010 |
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| DOI | 10.1007/978-3-642-17711-8_31 |
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| Discipline | Engineering Computer Science |
| EISBN | 3642177115 9783642177118 |
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| Editor | Ünay, Devrim Çataltepe, Zehra Aksoy, Selim |
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| PublicationTitle | Recognizing Patterns in Signals, Speech, Images and Videos |
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| SubjectTerms | activity recognition group action recognition Hough-voting human action recognition low-resolution video video analysis |
| Title | Variations of a Hough-Voting Action Recognition System |
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