Graph cut video object segmentation using histogram of oriented gradients

This paper introduces a novel way to implement graph cut for video object segmentation with shape information. Graph Cut is a very efficient algorithm for image segmentation and histogram of oriented gradients (HOG) is useful in detecting humans. We combine the HOG feature to incorporate a shape prior into graph cut algorithm as a new way to enhance video object segmentation accuracy. In previous work, we used a fully connected 3-D that is slow and is subject to weak edges, inconsistent luminance. The new method is compared with old methods to show that it helps by introducing a shape prior for segmentation of pre-trained objects such as humans.