Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Previous video matting approaches mostly adopt the “binary segmentation + matting” strategy, i.e., first segment each frame into foreground and background regions, then extract the fine details of the foreground boundary using matting techniques. This framework has several limitations due to the fact that binary segmentation is employed. ,  propose a new supervised video matting approach. Instead of applying binary segmentation,  explicitly model segmentation uncertainty in a novel tri-level segmentation procedure. The segmentation is done progressively, enabling us to handle difficult cases such as large topology changes, which are challenging to previous approaches. The tri-level segmentation results can be naturally fed into matting techniques to generate the final alpha mattes. Experimental results show that our system can generate high quality results with less user inputs than the state-of-the-art methods.
['Jinlong Ju', 'Jue Wang', 'Yebin Liu', 'Haoqian Wang', 'Qionghai Dai']
I am writing a research paper on a idea A Progressive Tri-level Segmentation Approach for Topology-Change-Aware Video Matting
[{"from": "human", "value": "I am writing a research paper on a idea A Progressive Tri-level Segmentation Approach for Topology-Change-Aware Video Matting"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Previous video matting approaches mostly adopt the \u201cbinary segmentation + matting\u201d strategy, i.e., first segment each frame into foreground and background regions, then extract the fine details of the foreground boundary using matting techniques. This framework has several limitations due to the fact that binary segmentation is employed. ,  propose a new supervised video matting approach. Instead of applying binary segmentation,  explicitly model segmentation uncertainty in a novel tri-level segmentation procedure. The segmentation is done progressively, enabling us to handle difficult cases such as large topology changes, which are challenging to previous approaches. The tri-level segmentation results can be naturally fed into matting techniques to generate the final alpha mattes. Experimental results show that our system can generate high quality results with less user inputs than the state-of-the-art methods."}]