Kanokphan Lertniphonphan

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Recognizing human actions is a challenging research area due to the complexity and variation of human's appearances and postures, the variation of camera settings, and angles. In this paper, we introduce a motion descriptor based on direction of optical flow for human action recognition. The directional value of a silhouette is divided into small regions.(More)
Human actions in video have the variation in both spatial and time domains which cause the difficulty for action classification. According to the nature of articulated body, an amount of movement from point-to-point is not constant, which can be illustrated as a bell-shape. In this paper, key frames are detected for specifying a starting and ending point(More)
Human action in the image sequence can be seen as the relation of the movement of body parts. Since, human has an articulated body, each body part cannot move freely. In each action, the specific directions of body parts arrangement cause a change in posture and movement over time. In this paper, the image oriented gradient and histogram of motion direction(More)
Human action movement has constrained by the articulated body which leads to the variation of movement velocity from point-to-point. In this paper, adaptive key frame intervals are used to specify the proper number of frames by detecting the variation of human motion. Features which are extracted within the interval contain information of primitive movement(More)
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