Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  introduce variational optical flow computation involving the prior with the fractional order differentiations. The fractional order differentiation is a typical tool in signal processing and image analysis. The zero crossing of a fractional order Laplacian yields a good performance for edge detection. As a sequel of edge detection with the fractional order differentiations,  deal with variational optical flow computation involving the fractional order differentiations on optical flow vectors. The method allows us to detect discontinuity of optical flow using linear operations.
['Koji Kashu', 'Atsushi Imiya', 'Tomoya Sakai']
I am writing a research paper on a idea Multiscale analysis of volumetric motion field using general order prior
[{"from": "human", "value": "I am writing a research paper on a idea Multiscale analysis of volumetric motion field using general order prior"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  introduce variational optical flow computation involving the prior with the fractional order differentiations. The fractional order differentiation is a typical tool in signal processing and image analysis. The zero crossing of a fractional order Laplacian yields a good performance for edge detection. As a sequel of edge detection with the fractional order differentiations,  deal with variational optical flow computation involving the fractional order differentiations on optical flow vectors. The method allows us to detect discontinuity of optical flow using linear operations."}]