Convex relaxation for a 3D spatiotemporal segmentation model using the primal-dual method  

作　　者：Shi-yan WANG Hui-min YU 

机构地区：[1]Department of Information Science&Electronic Engineering,Zhejiang University,Hangzhou 310027,China

出　　处：《Journal of Zhejiang University-Science C(Computers and Electronics)》2012年第6期428-439,共12页浙江大学学报C辑（计算机与电子（英文版）

基　　金：supported by the National Natural Science Foundation of China (No. 60872069);the National Basic Research Program (973)of China (No. 2012CB316400)

摘　　要：A method based on 3D videos is proposed for multi-target segmentation and tracking with a moving viewing system. A spatiotemporal energy functional is built up to perform motion segmentation and estimation simultaneously. To overcome the limitation of the local minimum problem with the level set method, a convex relaxation method is applied to the 3D spatiotemporal segmentation model. The relaxed convex model is independent of the initial condition. A primal-dual algorithm is used to improve computational efficiency. Several indoor experiments show the validity of the proposed method.A method based on 3D videos is proposed for multi-target segmentation and tracking with a moving viewing system. A spatiotemporal energy functional is built up to perform motion segmentation and estimation simultaneously. To overcome the limitation of the local minimum problem with the level set method, a convex relaxation method is applied to the 3 D spatiotemporal segmentation model. The relaxed convex model is independent of the initial condition. A primal-dual algorithm is used to improve computational efficiency. Several indoor experiments show the validity of the proposed method.

关 键 词：3D spatiotemporal segmentation Motion estimation Total variation PRIMAL-DUAL 

分 类 号：TP391.7[自动化与计算机技术—计算机应用技术] TP317.4[自动化与计算机技术—计算机科学与技术]