Complexity awareness based feature adaptive co-segmentation
Fanman Meng, Hongliang Li · 2013
In this paper, we achieve co-segmentation by learning adaptive feature model for each image group. A novel feature adaptive co-segmentation method and an image complexity awareness method are proposed. We also propose a linear feature model and an expectation-minimization (EM) based algorithm for adaptive feature learning. In the EM based algorithm, two aspects such as the accuracy confidence of the simple image segmentation and the fitness of the learned model to the simple image segmentation are considered. L1-regularized least squares optimization is also combined for the minimization. By testing on several well-known datasets, the error rates of the final co-segmentation are verified to be lower than the existing state-of-the-art co-segmentation methods.