Publicação
Human skeleton detection from semi-constrained environment video
| Resumo: | The correct classification of human skeleton from video is a key issue for the recognition of human actions and behavior. In this paper, we present a computational system for a passive detection of human star skeleton from raw video. The overall system is based on two main modules: segmentation and star skeleton detection. For each module, several computer vision methods were adjusted and tested under a comparative analysis that used a challenging video dataset (e.g., different daylight and weather conditions). The obtained results show that our system is capable of detecting human skeletons in most situations. |
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| Autores principais: | Afsar, Palwasha |
| Outros Autores: | Cortez, Paulo; Santos, Henrique |
| Assunto: | Human action Action recognition Video data Skeleton detection |
| Ano: | 2017 |
| País: | Portugal |
| Tipo de documento: | comunicação em conferência |
| Tipo de acesso: | acesso restrito |
| Instituição associada: | Universidade do Minho |
| Idioma: | inglês |
| Origem: | RepositóriUM - Universidade do Minho |
| Resumo: | The correct classification of human skeleton from video is a key issue for the recognition of human actions and behavior. In this paper, we present a computational system for a passive detection of human star skeleton from raw video. The overall system is based on two main modules: segmentation and star skeleton detection. For each module, several computer vision methods were adjusted and tested under a comparative analysis that used a challenging video dataset (e.g., different daylight and weather conditions). The obtained results show that our system is capable of detecting human skeletons in most situations. |
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