figure-groundsegmentation is used to extract the foreground from the background, where the foreground is usually defined as the region containing the most meaningful object of the image. In fact, the algorithms that ...
详细信息
figure-groundsegmentation is used to extract the foreground from the background, where the foreground is usually defined as the region containing the most meaningful object of the image. In fact, the algorithms that take advantage of humancomputer interaction often attain better performance and they are based on the 'one-to-one' model. In this study, the authors present a novel algorithm for figure-groundsegmentation based on the GrabCut algorithm, which is a common segmentationalgorithm that is user interactive. However, instead of a real user, they attempt to use a pre-trained deep convolutional neural network to interact with GrabCut for completing its job successfully. Weizmann's segmentation evaluation database is used as the test dataset and the results show that their algorithm works well for figure-groundsegmentation. While the previous automaticsegmentationalgorithms are required to rank their segments empirically in order to find the position of the foreground after the segmentation, their algorithm is fullyautomatic.
暂无评论