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Information Fusion for Multi-camera and Multi-body Structure and Motion

  • Alexander Andreopoulos
  • John K. Tsotsos
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4843)

Abstract

Information fusion algorithms have been successful in many vision tasks such as stereo, motion estimation, registration and robot localization. Stereo and motion image analysis are intimately connected and can provide complementary information to obtain robust estimates of scene structure and motion. We present an information fusion based approach for multi-camera and multi-body structure and motion that combines bottom-up and top-down knowledge on scene structure and motion. The only assumption we make is that all scene motion consists of rigid motion. We present experimental results on synthetic and non-synthetic data sets, demonstrating excellent performance compared to binocular based state-of-the-art approaches for structure and motion.

Keywords

Motion Estimation Information Fusion Image Motion Stereo Camera Best Linear Unbiased Estimator 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Alexander Andreopoulos
    • 1
  • John K. Tsotsos
    • 1
  1. 1.York University, Dept. of Computer Science & Engineering, Toronto, Ontario, M3J 1P3Canada

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