Segmentation of Sequences of Stereoscopic Images for Modelling Artificial Muscles

  • Authors:

  • Santiago González-Benítez;Rafael Verdú-Monedero;Rafael Berenguer-Vidal;Pedro García-Laencina

  • Affiliations:

  • Department of Information Technologies and Communications, Technical University of Cartagena, 30202, Cartagena, Spain;Department of Information Technologies and Communications, Technical University of Cartagena, 30202, Cartagena, Spain;Department of Technical Sciences, Catholic University of Murcia, 30107, Murcia, Spain;Department of Information Technologies and Communications, Technical University of Cartagena, 30202, Cartagena, Spain

  • Venue:
  • IWINAC '07 Proceedings of the 2nd international work-conference on Nature Inspired Problem-Solving Methods in Knowledge Engineering: Interplay Between Natural and Artificial Computation, Part II
  • Year:
  • 2007

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Abstract

In this paper, an implementation of the Region Competitionalgorithm for segmenting stereoscopic video sequences is shown. This algorithm is an essential task in the method in order to obtain a 3D characterization of artificial muscles. Image sequences are acquired by a two-cam computer vision system. Optimal and efficient segmentation of these images is our goal; information obtained from the segmented first frame of the video sequence is used for segmenting the next frame and so on. Redundancy between stereoscopic pairs of images is also used to optimize the segmentation. In this paper, the Region Competitionalgorithm is described and our own specific implementation is addressed. Particular problems of stereoscopic video segmentation are shown and how they are solved. Finally, results yielded from simulations are presented and conclusions close the paper.