Pixel-Based Object Detection and Tracking with Ensemble of Support Vector Machines and Extended Structural Tensor

  • Bogusław Cyganek
  • Michał Woźniak
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7653)


In this paper we propose a system for visual object detection and tracking based on the extended structural tensor and the ensemble of one-class support vector machines. First, the input color image is transformed with the anisotropic process into the extended structural tensor. Then the tensor space is clustered into the number of partitions which are used to train a corresponding number of one-class support vector machines composing an ensemble of classifiers. In run-time the ensemble classifies the input video stream into an object and background. Thanks to high discriminative properties of the extended structural tensor and to the diversity of the ensemble of classifiers the method shows very good properties which were shown by experiments on real video sequences.


Support Vector Machine Object Detection Anisotropic Diffusion Structural Tensor Tensor Space 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Bogusław Cyganek
    • 1
  • Michał Woźniak
    • 2
  1. 1.AGH University of Science and TechnologyKrakówPoland
  2. 2.Wroclaw University of TechnologyWrocławPoland

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