Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  propose a novel approach for video stabilization using Markov random field (MRF) modeling and maximum a posteriori (MAP) optimization.  build an MRF model describing a sequence of unstable images and find joint pixel matchings over all image sequences with MAP optimization via Gibbs sampling. The resulting displacements of matched pixels in consecutive frames indicate the camera motion beten frames and can be used to remove the camera motion to stabilize image sequences. The proposed method shows robust performance even when a scene has moving foreground objects and brings more accurate stabilization results. The performance of our algorithm is evaluated on outdoor scenes.
['Soo Wan Kim', 'Kwang Moo Yi', 'Songhwai Oh', 'Jin Young Choi']
I am writing a research paper on a idea Recovery Video Stabilization Using MRF-MAP Optimization
[{"from": "human", "value": "I am writing a research paper on a idea Recovery Video Stabilization Using MRF-MAP Optimization"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  propose a novel approach for video stabilization using Markov random field (MRF) modeling and maximum a posteriori (MAP) optimization.  build an MRF model describing a sequence of unstable images and find joint pixel matchings over all image sequences with MAP optimization via Gibbs sampling. The resulting displacements of matched pixels in consecutive frames indicate the camera motion beten frames and can be used to remove the camera motion to stabilize image sequences. The proposed method shows robust performance even when a scene has moving foreground objects and brings more accurate stabilization results. The performance of our algorithm is evaluated on outdoor scenes."}]