Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Automated face recognition is an application domain for au- tomatically identifying or verifying a person in a digital image or a video frame from a video source. This is becoming an increasingly important function in many areas ranging from static matching of controlled pho- tographs and credit card verification to surveillance video images. Hover for many years face recognition technology has been focused on one face: frontal, ll illuminated and looking directly at the capture device. In reality the situation is different. Human face is being vied in variety of poses, under a range of illumination conditions and chang- ing expression in real world. In recent years, a considerable number of researches have been carried out to deal with each of these forms of vari- ations individually. Hover combining techniques to deal with multiple forms of variation at once has received less scrutiny. In this research  utilize two established techniques which cater for these forms of varia- tions individually and unify them into a single novel algorithm for better recognition of human faces.
['Ayesha Kurukulasooriya', 'Anuja T. Dharmarathne']
I am writing a research paper on a idea Image Searching with Eigenfaces and Facial Characteristics
[{"from": "human", "value": "I am writing a research paper on a idea Image Searching with Eigenfaces and Facial Characteristics"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Automated face recognition is an application domain for au- tomatically identifying or verifying a person in a digital image or a video frame from a video source. This is becoming an increasingly important function in many areas ranging from static matching of controlled pho- tographs and credit card verification to surveillance video images. Hover for many years face recognition technology has been focused on one face: frontal, ll illuminated and looking directly at the capture device. In reality the situation is different. Human face is being vied in variety of poses, under a range of illumination conditions and chang- ing expression in real world. In recent years, a considerable number of researches have been carried out to deal with each of these forms of vari- ations individually. Hover combining techniques to deal with multiple forms of variation at once has received less scrutiny. In this research  utilize two established techniques which cater for these forms of varia- tions individually and unify them into a single novel algorithm for better recognition of human faces."}]