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Symeon Nikitidis
Researcher at Aristotle University of Thessaloniki
Publications - 16
Citations - 199
Symeon Nikitidis is an academic researcher from Aristotle University of Thessaloniki. The author has contributed to research in topics: Non-negative matrix factorization & Multiple discriminant analysis. The author has an hindex of 8, co-authored 16 publications receiving 186 citations. Previous affiliations of Symeon Nikitidis include Imperial College London.
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Journal ArticleDOI
Subclass discriminant Nonnegative Matrix Factorization for facial image analysis
TL;DR: The proposed method incorporates appropriate discriminant constraints in the NMF decomposition cost function in order to address the problem of finding discriminant projections that enhance class separability in the reduced dimensional projection space, while taking into account subclass information.
Journal ArticleDOI
Maximum Margin Projection Subspace Learning for Visual Data Analysis
TL;DR: The proposed method, called maximum margin projection pursuit, aims to identify a low dimensional projection subspace, where samples form classes that are better discriminated, i.e., are separated with maximum margin.
Proceedings ArticleDOI
Learning Slow Features for Behaviour Analysis
TL;DR: A novel deterministic SFA algorithm that is able to identify linear projections that extract the common slowest varying features of two or more sequences and an Expectation Maximization algorithm to perform inference in a probabilistic formulation of SFA are proposed.
Journal ArticleDOI
Probabilistic Slow Features for Behavior Analysis
TL;DR: A novel deterministic SFA algorithm that is able to identify linear projections that extract the common slowest varying features of two or more sequences and an expectation maximization algorithm to perform inference in a probabilistic formulation of SFA are proposed.
Journal ArticleDOI
Camera Motion Estimation Using a Novel Online Vector Field Model in Particle Filters
TL;DR: A novel stochastic vector field model is proposed, which can handle smooth motion patterns derived from long periods of stable camera motion and can also cope with rapid camera motion changes and periods when the camera remains still.