Data-driven hair segmentation with isomorphic manifold inference
作者：
Highlights：
• Similar coarse hair probability maps should correspond to similar segmentations.
• Data-driven Isomorphic Manifold Inference is proposed to exploit the shape priors.
• We integrate the inferred shape, color and texture into a unified framework.
• Besides hair segmentation, we also validate our IMI on horse class segmentation.
• Experiments on hair and horse databases show impressive performances.
摘要
•Similar coarse hair probability maps should correspond to similar segmentations.•Data-driven Isomorphic Manifold Inference is proposed to exploit the shape priors.•We integrate the inferred shape, color and texture into a unified framework.•Besides hair segmentation, we also validate our IMI on horse class segmentation.•Experiments on hair and horse databases show impressive performances.
论文关键词：Hair segmentation,Data driven,Shape model,Isomorphic manifold inference
论文评审过程：Received 8 June 2013, Revised 28 November 2013, Accepted 25 February 2014, Available online 11 March 2014.
论文官网地址：https://doi.org/10.1016/j.imavis.2014.02.011
