Can Motion Segmentation Improve Patch-based Object Recognition?

Adrian Ulges, Thomas Breuel
Proceedings of the 20th International Conference on Pattern Recognition, Istanbul, Turkey, IEEE, 2010

Abstract:

Patch-based methods, which constitute the state of the art in object recognition, are often applied to video data, where motion information provides a valuable clue for separating objects of interest from the background. We show that such motion-based segmentation improves the robustness of patch-based recognition with respect to clutter. Our approach ­ which employs segmentation information to rule out incorrect correspondences between training and test views ­ is demonstrated to distinctly outperform baselines operating on unsegmented images. Relative improvements reach 50% for the recognition of specific objects, and 33% for object category retrieval.

Files:

  paper.pdf

BibTex:

@inproceedings{ ULGE2010,
	Title = {Can Motion Segmentation Improve Patch-based Object Recognition?},
	Author = {Adrian Ulges and Thomas Breuel},
	BookTitle = {Proceedings of the 20th International Conference on Pattern Recognition},
	Year = {2010},
	Publisher = {IEEE}
}

     
Last modified:: 30.08.2016