Abstract
A novel contour-constrained superpixel (CCS) algorithm
is proposed in this work. We initialize superpixels and regions in a regular grid and then refine the superpixel label of each region hierarchically from block to pixel levels.
To make superpixel boundaries compatible with object contours, we propose the notion of contour pattern matching
and formulate an objective function including the contour
constraint. Furthermore, we extend the CCS algorithm to
generate temporal superpixels for video processing. We initialize superpixel labels in each frame by transferring those
in the previous frame and refine the labels to make superpixels temporally consistent as well as compatible with object contours. Experimental results demonstrate that the
proposed algorithm provides better performance than the
state-of-the-art superpixel methods.