Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: , a novel discriminant feature extraction algorithm employing center-based distance is proposed for face recognition. This new method, which is a supervised linear dimensionality reduction and feature extraction approach, computes the center-based distance beten each training sample-pairs in the same class and the distance beten each training sample-pair belonging to different classes. Then the high-dimensional data are embedded into a low-dimensional space, preserving the within-class geometric structure on a submanifold via maximum variance projection. Many experiments on ORL and Yale face database indicate that this method is highly effective.
['Hui Yan', 'W. Yang', 'Jian Yang', 'Jingyu Yang']
I am writing a research paper on a idea Discriminant feature extraction based on center distance
[{"from": "human", "value": "I am writing a research paper on a idea Discriminant feature extraction based on center distance"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: , a novel discriminant feature extraction algorithm employing center-based distance is proposed for face recognition. This new method, which is a supervised linear dimensionality reduction and feature extraction approach, computes the center-based distance beten each training sample-pairs in the same class and the distance beten each training sample-pair belonging to different classes. Then the high-dimensional data are embedded into a low-dimensional space, preserving the within-class geometric structure on a submanifold via maximum variance projection. Many experiments on ORL and Yale face database indicate that this method is highly effective."}]