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Stephen J. Maybank
Researcher at Birkbeck, University of London
Publications - 172
Citations - 17723
Stephen J. Maybank is an academic researcher from Birkbeck, University of London. The author has contributed to research in topics: Video tracking & Motion estimation. The author has an hindex of 50, co-authored 166 publications receiving 15225 citations. Previous affiliations of Stephen J. Maybank include University of Oxford & University of Reading.
Papers
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Journal ArticleDOI
A survey on visual surveillance of object motion and behaviors
TL;DR: This paper reviews recent developments and general strategies of the processing framework of visual surveillance in dynamic scenes, and analyzes possible research directions, e.g., occlusion handling, a combination of two and three-dimensional tracking, and fusion of information from multiple sensors, and remote surveillance.
Journal ArticleDOI
General Tensor Discriminant Analysis and Gabor Features for Gait Recognition
TL;DR: A general tensor discriminant analysis (GTDA) is developed as a preprocessing step for LDA for face recognition and achieves good performance for gait recognition based on image sequences from the University of South Florida (USF) HumanID Database.
Journal ArticleDOI
Knowledge Distillation: A Survey
TL;DR: A comprehensive survey of knowledge distillation from the perspectives of knowledge categories, training schemes, teacher-student architecture, distillation algorithms, performance comparison and applications can be found in this paper.
Book ChapterDOI
Camera Self-Calibration: Theory and Experiments
TL;DR: It is shown, using experiments with noisy data, that it is possible to calibrate a camera just by pointing it at the environment, selecting points of interest and then tracking them in the image as the camera moves.
Journal ArticleDOI
A theory of self-calibration of a moving camera
TL;DR: The feasibility of camera calibration based on the epipolar transformation is demonstrated and two curves of degree six can be obtained in the dual plane such that one of the real intersections of the two yields the correct camera calibration.