Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A new technique for face recognition - Ridgefaces - is presented. The method combines the ll-known Fisherface method with the ridgelet transform and high-speed Photometric Stereo (PS). The paper first derives ridgelet projections for 2D/2.5D face images before the Fisherface approach is used to reduce the dimensionality and increase the spread of the resulting feature vectors. The ridgelet transform is attractive because it is efficient at extracting highly discriminating low-frequency directional features. Best recognition is obtained when Ridgefaces is performed on surface normals acquired from PS, although good results are also found using standard 2D images and PS-derived albedo maps.
['Satyajit N. Kautkar', 'Gary A. Atkinson', 'Melvyn L. Smith']
I am writing a research paper on a idea Face recognition in 2D and 2.5D using ridgelets and photometric stereo
[{"from": "human", "value": "I am writing a research paper on a idea Face recognition in 2D and 2.5D using ridgelets and photometric stereo"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A new technique for face recognition - Ridgefaces - is presented. The method combines the ll-known Fisherface method with the ridgelet transform and high-speed Photometric Stereo (PS). The paper first derives ridgelet projections for 2D/2.5D face images before the Fisherface approach is used to reduce the dimensionality and increase the spread of the resulting feature vectors. The ridgelet transform is attractive because it is efficient at extracting highly discriminating low-frequency directional features. Best recognition is obtained when Ridgefaces is performed on surface normals acquired from PS, although good results are also found using standard 2D images and PS-derived albedo maps."}]