DEPTH PREDICTION AT HOMOGENEOUS IMAGE STRUCTURES

Kalkan S., Wörgötter F., Kruger N.

Proceedings of the Third International Conference on Computer Vision Theory and Applications, Funchal, Portugal, 22 - 25 January 2008, pp.520-527

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.5220/0001079005200527
  • City: Funchal
  • Country: Portugal
  • Page Numbers: pp.520-527
  • Middle East Technical University Affiliated: No

Abstract

This paper proposes a voting-based model that predicts depth at weakly-structured image areas from the depth that is extracted using a feature-based stereo method. We provide results, on both real and artificial scenes, that show the accuracy and robustness of our approach. Moreover, we compare our method to different dense stereo algorithms to investigate the effect of texture on performance of the two different approaches. The results confirm the expectation that dense stereo methods are suited better for textured image areas and our method for weakly-textured image areas.