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- W3100524350 abstract "Human motion analysis using computer vision has received increasing attention and applied in various fields. Its main task is to detect, extract, and represent human motion information from video. We introduce an approach that takes advantage of computer vision in motion recognition based on gait segmentation and template comparison to evaluate the motion of models in scene of fashion show. The method we proposed extracts joint position information of moving objects in each frame directly from the input video stream first. Then, it extracts angle features in the sequence of motion and segments the sequence by operations of dimension reduction, filtering, and peak detection. Finally, it aligns the segmentation and template sequences by dynamic time warping (DTW) in combination with Procrustes analysis and computes distances that are used as features for classification. The results show clear differences between professional and amateur models. The proposed method has great potential in providing qualitative evaluation of models’ postures." @default.
- W3100524350 created "2020-11-23" @default.
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- W3100524350 date "2020-11-18" @default.
- W3100524350 modified "2023-09-27" @default.
- W3100524350 title "The Action Evaluation of Model Catwalk Based on Gait Segmentation and Template Comparison" @default.
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- W3100524350 doi "https://doi.org/10.1007/978-981-15-5887-0_60" @default.
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