Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Unconstrained face recognition is the problem of deciding if an image pair is showing the same individual or not, without having class specific training material or knowing anything about the image conditions. , an approach of learning suited similarity measurements is introduced. For this the image is partitioned into several parts, to extract image region based histograms of gradients, local binary patterns and three patch local binary patterns. The similarities of respective patches are computed and it is learnt how to ight the different image regions. Finally, a fusion is applied using a Multi Layer Perceptron. Evaluations are done on the “Labeled Faces in the Wild” dataset.
['Andre Stormer', 'Gerhard Rigoll']
I am writing a research paper on a idea Learning weighted similarity measurements for unconstrained face recognition
[{"from": "human", "value": "I am writing a research paper on a idea Learning weighted similarity measurements for unconstrained face recognition"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Unconstrained face recognition is the problem of deciding if an image pair is showing the same individual or not, without having class specific training material or knowing anything about the image conditions. , an approach of learning suited similarity measurements is introduced. For this the image is partitioned into several parts, to extract image region based histograms of gradients, local binary patterns and three patch local binary patterns. The similarities of respective patches are computed and it is learnt how to ight the different image regions. Finally, a fusion is applied using a Multi Layer Perceptron. Evaluations are done on the \u201cLabeled Faces in the Wild\u201d dataset."}]