Search Results - Computer Vision and Image Understanding
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Foul prediction with estimated poses from soccer broadcast video
Fang, J., Yeung, C., Fujii, K.Published in Sports Engineering (2025)“…Recent advances in computer vision have led to significant progress in tracking and pose estimation of sports players. …”
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Temporal pattern attention for multivariate time series of tennis strokes classification
Skublewska-Paszkowska, M., Powroznik, P.Published in Sensors (2023)“…It interacts with many aspects of Computer Vision, Machine Learning, Deep Learning and Image Processing in order to understand human behaviours as well as identify them. …”
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Multi-object tracking by flying cameras based on a forward-backward interaction
Carletti, V., Greco, A., Saggese, A., Vento, M.Published in IEEE Access (2018)“…The automatic analysis of images acquired by cameras mounted on board of drones (flying cameras) is attracting many scientists working in the field of computer vision; the interest is related to the increasing need of algorithms able to understand the scenes acquired by flying cameras, by detecting the moving objects, calculating their trajectories and finally understanding their activities. …”
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Human Motion: Understanding, Modelling, Capture and Animation
B. Rosenhahn, R. Klette, D. MetaxasPublished 2008 -
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A survey of advances in vision-based human motion capture and analysis
Moeslund, T. B., Hilton, A., Krüger, V.Published in Computer Vision and Image Understanding (2006)“…Computer Vision and Image Understanding…”
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Special issue on modeling people: Vision-based understanding of a person`s shape, appearance, movement and behaviour
Published in Computer Vision and Image Understanding (2006)“…Computer Vision and Image Understanding…”
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Computer analysis systems of performance in team sports
Carling, C.Published in Expertise in Elite sport. 2nd International Days of Sport Sciences, 12.-15. November 2002, INSEP, Paris (France) (2002)“…A multi-camera system combined with a high-tech computer vision program based on digital image processing techniques and mathematical algorithms provides over 4 million bits of information per match (Carling, 2002). …”