This paper presents an extension to the popular fuzzy c-means clustering method by introducing an additional disparity cue. The creation of the clusters is driven by a degree of the stereo match and thus is able to separate the objects based on their different colour and spatial depth. #R##N##R##N#In contrast to the other popular approaches, the clustering is not performed on the individual input images, but on the stereo pair, and takes into account the matching properties. The algorithm is capable of producing the segmentations, as well as the disparity maps. The results of this algorithm show that the proposed method can improve the segmentation, under the condition of having the stereo image pair of the segmented scene.
['Michal Krumnikl', 'Eduard Sojka', 'Jan Gaura']
Modified Fuzzy C-Means as a Stereo Segmentation Method