Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  address the problem of egomotion estimation of a monocular observer moving with arbitrary translation and rotation in an unknown environment, using log-polar images. The method  propose is uniquely based on the spatio-temporal image derivatives, or the normal flow. Thus,  avoid computing the complete optical flow field, which is an ill-posed problem due to the aperture problem.  use a search paradigm based on geometric properties of the normal flow field, and consider a family of search subspaces to estimate the egomotion parameters. These algorithms are particularly ll-suited for the log-polar image geometry, as  use a selection of special normal flow, vectors with simple representation in log-polar coordinates. This approach highlights the close coupling beten algorithmic aspects and the sensor geometry (retina physiology), often, found in nature. Finally,  present and discuss a set of experiments, for various kinds of camera motions, which show encouraging results.
['César Silva', 'José Santos-Victor']
I am writing a research paper on a idea Egomotion estimation using log-polar images
[{"from": "human", "value": "I am writing a research paper on a idea Egomotion estimation using log-polar images"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  address the problem of egomotion estimation of a monocular observer moving with arbitrary translation and rotation in an unknown environment, using log-polar images. The method  propose is uniquely based on the spatio-temporal image derivatives, or the normal flow. Thus,  avoid computing the complete optical flow field, which is an ill-posed problem due to the aperture problem.  use a search paradigm based on geometric properties of the normal flow field, and consider a family of search subspaces to estimate the egomotion parameters. These algorithms are particularly ll-suited for the log-polar image geometry, as  use a selection of special normal flow, vectors with simple representation in log-polar coordinates. This approach highlights the close coupling beten algorithmic aspects and the sensor geometry (retina physiology), often, found in nature. Finally,  present and discuss a set of experiments, for various kinds of camera motions, which show encouraging results."}]