Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The depth image based rendering (DIBR) plays a key role in 3D video synthesis, by which other virtual views can be generated from a 2D video and its depth map. Hover, in the synthesis process, the background occluded by the foreground objects might be exposed in the new view, resulting in some holes in the synthetized video. , a hole filling approach based on background reconstruction is proposed, in which the temporal correlation information in both the 2D video and its corresponding depth map are exploited to construct a background video. To construct a clean background video, the foreground objects are detected and removed. Also motion compensation is applied to make the background reconstruction model suitable for moving camera scenario. Each frame is projected to the current plane where a modified Gaussian mixture model is performed. The constructed background video is used to eliminate the holes in the synthetized video. Our experimental results have indicated that the proposed approach has better quality of the synthetized 3D video compared with the other methods.
['Guibo Luo', 'Yuesheng Zhu', 'Zhaotian Li', 'Liming Zhang']
I am writing a research paper on a idea A Hole Filling Approach Based on Background Reconstruction for View Synthesis in 3D Video
[{"from": "human", "value": "I am writing a research paper on a idea A Hole Filling Approach Based on Background Reconstruction for View Synthesis in 3D Video"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The depth image based rendering (DIBR) plays a key role in 3D video synthesis, by which other virtual views can be generated from a 2D video and its depth map. Hover, in the synthesis process, the background occluded by the foreground objects might be exposed in the new view, resulting in some holes in the synthetized video. , a hole filling approach based on background reconstruction is proposed, in which the temporal correlation information in both the 2D video and its corresponding depth map are exploited to construct a background video. To construct a clean background video, the foreground objects are detected and removed. Also motion compensation is applied to make the background reconstruction model suitable for moving camera scenario. Each frame is projected to the current plane where a modified Gaussian mixture model is performed. The constructed background video is used to eliminate the holes in the synthetized video. Our experimental results have indicated that the proposed approach has better quality of the synthetized 3D video compared with the other methods."}]