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- W2805118380 abstract "This paper proposes to extend the framework presented in [1]. In this paper, we proposed to label the upper body pose in the acquired multiview images. These human pose can be used to represent different body action, such as punching, which involve upper arm to be further from the body. Our extended framework here focuses on the upper body parts especially actions involving the upper and lower hand(s). Two steps were added to the previous framework, namely, (1) pose estimation, and (2) hand action classification. Here, we employ a simple estimation method, where three points will be identified, namely, shoulder S, elbow E and wrist W, forming two lines. In the hand action classification, this paper focuses on three types of hand actions, namely (1) HSS (hand stretching), HNS (hand not stretching). For this, the k-means clustering is being employed, whereby, images from different view (front camera, left camera and right camera) will be classified into one of the two possible action. Preliminary results show that our proposed framework is quite promising in classifying the upper body actions." @default.
- W2805118380 created "2018-06-13" @default.
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- W2805118380 date "2018-01-01" @default.
- W2805118380 modified "2023-10-17" @default.
- W2805118380 title "Upper body action classification for multiview images using K-means" @default.
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- W2805118380 doi "https://doi.org/10.1109/iwait.2018.8369736" @default.
- W2805118380 hasPublicationYear "2018" @default.
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