Graph cut video object segmentation using histogram of oriented gradients
Chun‐Hao Wang, Ling Guan · 2008
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.