Handheld object detection and its related event analysis using ratio histogram and mixture of HMMs
| Autor: | Duan-Yu Chen, Li-Chih Chen, Jun-Wei Hsieh, Chi-Hung Chuang, Jiun-Chen Cheng |
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| Rok vydání: | 2014 |
| Předmět: |
business.industry
Event (computing) Computer science Process (computing) Brute-force search Pattern recognition Context (language use) Object detection Histogram Signal Processing Media Technology Computer vision Computer Vision and Pattern Recognition Artificial intelligence Electrical and Electronic Engineering business Representation (mathematics) Mobile device |
| Zdroj: | Journal of Visual Communication and Image Representation. 25:1399-1415 |
| ISSN: | 1047-3203 |
| DOI: | 10.1016/j.jvcir.2014.05.009 |
| Popis: | This paper proposes a novel system to analyze human-object interaction events happening between hands and faces in real time. Two challenging problems in this event analysis must be addressed, i.e., there is no prior knowledge (like shape, color, size, and texture) about the handheld objects, and there are large spatial-temporal variations in event representation. For the first challenge, a novel ratio histogram is proposed to find important color bins to locate handheld objects and their trajectories via a code book technique. This scheme is different from other boosted methods which require very time-consuming estimations to search reliable body configurations. For the second challenge, a mixture of HMMs is proposed to describe an event not only from its dynamic context but also its multiplicity context. It can be performed in real time because an exhaustive search process is avoided to find possible interaction pairs between objects and body parts. |
| Databáze: | OpenAIRE |
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