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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
Gait Components and Their Application to Gender Recognition
TL;DR: This paper analyzes the effectiveness of the seven human gait components for ID and gender recognition under a wide range of circumstances.
Journal ArticleDOI
Principal axis-based correspondence between multiple cameras for people tracking
TL;DR: A simple and robust method, based on principal axes of people, to match people across multiple cameras, according to the relationship between "ground-points" of people detected in each camera view and the intersections of principal axes detected in different camera views and transformed to the same view.
Journal ArticleDOI
Multi-modal Curriculum Learning for Semi-supervised Image Classification.
TL;DR: A well-organized propagation process leveraging multiple teachers and one learner enables the multi-modal curriculum learning (MMCL) strategy to outperform five state-of-the-art methods on eight popular image data sets.
Journal ArticleDOI
Manifold Regularized Multitask Learning for Semi-Supervised Multilabel Image Classification
TL;DR: A manifold regularized multitask learning (MRMTL) algorithm that effectively controls the model complexity because different tasks limit one another's search volume, and the manifold regularization ensures that the functions in the shared hypothesis space are smooth along the data manifold.
Book ChapterDOI
Fusion of Multiple Tracking Algorithms for Robust People Tracking
TL;DR: This paper shows how the output of a number of detection and tracking algorithms can be fused to achieve robust tracking of people in an indoor environment.