Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A methodology for accurate determination of surface normals and light source location from depth and reflectance data is introduced. Estimation of local surface orientation using depth data alone from range finders with standard depth errors can produce significant error, while shape-from-shading using reflectance data alone produces approximate surface orientation results that are highly dependent on the correct initial surface orientation estimates and regularization parameters. Combining these two sources of information gives vastly more accurate surface orientation estimates under general conditions than either one alone, and can also provide better knowledge of local curvature. Novel iterative methods that enforce satisfaction of the image irradiance equation and surface integrability without using regularization are proposed. These iterative methods work when the light source is any finite distance from the object, producing variable incident light orientation over the object. >
['Todd A. Mancini', 'Lawrence B. Wolff']
I am writing a research paper on a idea 3 D shape and light source location from depth and reflectance
[{"from": "human", "value": "I am writing a research paper on a idea 3 D shape and light source location from depth and reflectance"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A methodology for accurate determination of surface normals and light source location from depth and reflectance data is introduced. Estimation of local surface orientation using depth data alone from range finders with standard depth errors can produce significant error, while shape-from-shading using reflectance data alone produces approximate surface orientation results that are highly dependent on the correct initial surface orientation estimates and regularization parameters. Combining these two sources of information gives vastly more accurate surface orientation estimates under general conditions than either one alone, and can also provide better knowledge of local curvature. Novel iterative methods that enforce satisfaction of the image irradiance equation and surface integrability without using regularization are proposed. These iterative methods work when the light source is any finite distance from the object, producing variable incident light orientation over the object. >"}]