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This paper presents an upper body tracking algorithm with a single monocular camera. In order to be suitable for human robot interaction, the designed method should be free to work on the moving camera platform and also can achieve real-time performance. The dimension of human posture model is extremely high, and we hereby focus on the visual extraction of head and arms. A hierarchical structure model...
This research presents an upper body tracking method with a monocular camera. The human model is defined in a high dimensional state space. We hereby propose a hierarchical structure model to solve the tracking problem by SIR (Sampling Importance Resampling) particle filter with partitioned sampling. The image spatial and temporal information is used to track the human body and estimate the human...
Tracking the pose of human face has long been an important research topic which has many important applications, and it is particularly challenging with a monocular camera because the depth information is lost due to the perspective projection. This work adopts particle filter with partitioned sampling to decompose the state space of face pose tracking into two subspaces for increasing the sampling...
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