Synergism in low level vision

By C. M. Christoudias, Bogdan Georgescu, Peter Meer. Object recognition supported by user interaction for service robots, 2002

506 citations recorded by the source corpus.

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Frequency-tuned salient region detection (2009, methodology): “First, we replace the hill-climbing based k-means segmentation algorithm by the mean-shift segmentation algorithm [5], which provides better segmentation boundaries.”
Gaze-based interaction for semi-automatic photo cropping (2006, methodology): “The fine- and coarse-scale segmentations, Sfine and Scoarse, are produced by downsampling the photograph by a factor of 4 and 8, respectively, and performing a segmentation using EDISON [6].”
Region-Based Saliency Detection and Its Application in Object Recognition (2014, methodology): “Given an input image, we perform mean shift algorithm [13] in Lab color space to extract superpixels.”
Toward Objective Evaluation of Image Segmentation Algorithms (2007, methodology): “The only other paper using mean shift segmentation that speaks directly to the clustering is [20].”
Minimization of Region-Scalable Fitting Energy for Image Segmentation (2008, background): “The third term is called a level set regularization term, since it serves to maintain the regularity of the level set function.”
Robust Object Recognition with Cortex-Like Mechanisms (2007, methodology): “This was accomplished using the segmentation software Edison [54].”