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A Fast Joint Bioinspired Algorithm for Optic Flow and Two-Dimensional Disparity Estimation

  • Manuela Chessa
  • Silvio P. Sabatini
  • Fabio Solari
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5815)

Abstract

The faithful detection of the motion and of the distance of the objects in the visual scene is a desirable feature of any artificial vision system designed to operate in unknown environments characterized by conditions variable in time in an often unpredictable way. Here, we propose a distributed neuromorphic architecture, that, by sharing the computational resources to solve the stereo and the motion problems, produces fast and reliable estimates of optic flow and 2D disparity. The specific joint design approach allows us to obtain high performance at an affordable computational cost. The approach is validated with respect to the state-of-the-art algorithms and in real-world situations.

Keywords

Optic Flow Stereo Camera Binocular Disparity Population Code Vertical Disparity 
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 2009

Authors and Affiliations

  • Manuela Chessa
    • 1
  • Silvio P. Sabatini
    • 1
  • Fabio Solari
    • 1
  1. 1.Department of Biophysical and Electronic EngineeringUniversity of GenoaGenovaItaly

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