Multiresolution co-clustering for uncalibrated multiview segmentation

作者：

Highlights：

• A technique for coherently co-clustering uncalibrated views of a scene with a contour-based representation is presented.

• Motion information has been considered both for region adjacency and region similarity.

• A two-step iterative architecture is proposed to increase the partition solution space.

• A feasible global optimization that allows to jointly process all the views has been implemented.

摘要

•A technique for coherently co-clustering uncalibrated views of a scene with a contour-based representation is presented.•Motion information has been considered both for region adjacency and region similarity.•A two-step iterative architecture is proposed to increase the partition solution space.•A feasible global optimization that allows to jointly process all the views has been implemented.

论文关键词：Image segmentation,Object segmentation,Multiview segmentation,Co-clustering techniques

论文评审过程：Received 13 March 2018, Revised 15 April 2019, Accepted 15 April 2019, Available online 4 May 2019, Version of Record 14 May 2019.

论文官网地址：https://doi.org/10.1016/j.image.2019.04.010