Unsupervised dynamic texture segmentation using local descriptors in volumes

Dynamic texture (DT) is an extension of texture to the temporal domain. How to improve the performance and efficiency of DT segmentation is still a challenging problem. In this paper, we improve the performance of a recently published DT segmentation method. We compute the histogram of the spatiotemporal local texture descriptor in one volume and employ the segmentation results of previous frame for the segmentation of the current frame. Experimental results show that our approach improves the performance and efficiency of DT segmentation compared to the state-of-the-art methods.