Selection and Fusion of Multiple Stereo Algorithms for Accurate Disparity Segmentation

Creative Commons License

Bilgin A., ULUSOY İ.

IEEE 17th Signal Processing and Communications Applications Conference, Antalya, Turkey, 9 - 11 April 2009, pp.53-56 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/siu.2009.5136420
  • City: Antalya
  • Country: Turkey
  • Page Numbers: pp.53-56
  • Middle East Technical University Affiliated: Yes


Fusion of multiple stereo algorithms is performed in order to obtain accurate disparity segmentation in this study. Reliable disparity map of real-time stereo images is estimated and disparity segmentation is performed for object detection purpose. First, stereo algorithms which have high performance in real-time applications are chosen among the algorithms in the literature and three of them are implemented. Then, the results of these algorithms are fused to gain better performance in disparity estimation. In fusion process, if a pixel has the same disparity, value in all algorithms, that disparity value is assigned to the pixel. Other pixels are labelled as unknown disparity. Then, unknown disparity values are estimated by a refinement procedure where neighbourhood disparity information is used. Finally, the resultant disparity map is segmented by using mean shift segmentation.