Other variants:What is segmentation? >Segmentation =partitioning Grouping clustering Carve dense data set into (disjoint)regions Gather sets of items according to some model Divide image based on pixel similarity If items are dense,then essentially the same problem as Divide spatiotemporal volume based on image left.(e.g.,clustering pixels) similarity (shot detection) If items are sparse,then problem has a slightly different Figure/ground separation(background flavor: subtraction) Collect tokens that lie on a line (robust line fitting) Regions can be overlapping (layers) Collect pixels that share the same fundamental matrix (independent 3D rigid motion) Group 3D surface elements that belong to the same surface S.Birchfield,Clemson Univ.,ECE 847,http://www.cos.clomson.odu/-stb/oco847 Hag3 hou Dianzi Universit内抗州电子科技大学 School of Computer Science and Tecfnology计算机学院周文晖Hangzhou Dianzi University 杭州电子科技大学 School of Computer Science and Technology 计算机学院 周文晖 Other variants：What is segmentation?  Segmentation = partitioning  Carve dense data set into (disjoint) regions  Divide image based on pixel similarity  Divide spatiotemporal volume based on image similarity (shot detection)  Figure / ground separation (background subtraction)  Regions can be overlapping (layers) S. Birchfield, Clemson Univ., ECE 847, http://www.ces.clemson.edu/~stb/ece847  Grouping = clustering  Gather sets of items according to some model  If items are dense, then essentially the same problem as left. (e.g., clustering pixels)  If items are sparse, then problem has a slightly different flavor: • Collect tokens that lie on a line (robust line fitting) • Collect pixels that share the same fundamental matrix (independent 3D rigid motion) • Group 3D surface elements that belong to the same surface