2013/01/08 by Camille Couprie, Clément Farabet, Couprie, Camille +3
Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Medical Image Segmentation Techniques #Topological and Geometric Data Analysis #Visual Attention and Saliency Detection #cs.CV
paper · pdf · doi:10.48550/arxiv.1301.1671
6 pages, 5 figures
arxiv created 2013/01/08 · openalex publication_date 2013/01/08 · arxiv updated 2013/01/09 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Numerous approaches in image processing and computer vision are making use of super-pixels as a pre-processing step. Among the different methods producing such over-segmentation of an image, the graph-based approach of Felzenszwalb and Huttenlocher is broadly employed. One of its interesting properties is that the regions are computed in a greedy manner in quasi-linear time. The algorithm may be trivially extended to video segmentation by considering a video as a 3D volume, however, this can not be the case for causal segmentation, when subsequent frames are unknown. We propose an efficient video segmentation approach that computes temporally consistent pixels in a causal manner, filling the need for causal and real time applications.