Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  propose a vector representation (called a 3D signature) for 3D face shape in biometrics applications. Elements of the vector correspond to fixed surface points in a face-centered coordinate system. Since the elements are registered to the face, comparisons of vectors to produce match scores can be performed without a probe to gallery alignment step such as an invocation of the iterated closest point (ICP) algorithm in the calculation of each match score. The proposed 3D face recognition method employing the 3D signature ran more than three orders of magnitude faster than a traditional ICP based distance implementation, without sacrificing accuracy. As a result, it is feasible to apply distance based 3D face biometrics to recognition scenarios that, because of computational constraints, may have previously been limited to verification. Our use of more complex shape regions, which is a trivial task with the use of 3D signatures, improves biometric performance over simple spherical cut regions used previously [1]. Experimental results with a large database of 3D images demonstrate the technique and its advantages.
['Chris Boehnen', 'Tanya Peters', 'Patrick J. Flynn']
I am writing a research paper on a idea 3D Signatures for Fast 3D Face Recognition
[{"from": "human", "value": "I am writing a research paper on a idea 3D Signatures for Fast 3D 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:  propose a vector representation (called a 3D signature) for 3D face shape in biometrics applications. Elements of the vector correspond to fixed surface points in a face-centered coordinate system. Since the elements are registered to the face, comparisons of vectors to produce match scores can be performed without a probe to gallery alignment step such as an invocation of the iterated closest point (ICP) algorithm in the calculation of each match score. The proposed 3D face recognition method employing the 3D signature ran more than three orders of magnitude faster than a traditional ICP based distance implementation, without sacrificing accuracy. As a result, it is feasible to apply distance based 3D face biometrics to recognition scenarios that, because of computational constraints, may have previously been limited to verification. Our use of more complex shape regions, which is a trivial task with the use of 3D signatures, improves biometric performance over simple spherical cut regions used previously [1]. Experimental results with a large database of 3D images demonstrate the technique and its advantages."}]