Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  proposes a method to classify whether a landmark, which consists of the outline in a face shape model in the shape model based approaches, is properly fitted to feature points. Through this method, the reliability of information can be determined in the process of managing and using the shape. The enlarged face image by image sensor is processed by bilinear interpolation.  use the gray-value variance that considers the texture feature of skin for classification of landmarks. The gray-value variance is calculated in skin area of the patch constructed around the landmark. In order to make a system strong to poses,  project the image of face to the frontal face shape model. And, to fill out each area, the area with insufficient pixel information is filled out with bilinear interpolation. When the fitting is properly done, it has the variance with a low value to be calculated for smooth skin texture. On the other hand, the variance for misaligned landmark shows a high variance by the background and facial contour gradient.  have proposed a classifier using this characteristic and, as a result, classified the true and false in the landmark with an accuracy of 83.32% through the patch classifier.
['Seokhoon Kang', 'Seonwoon Kim']
I am writing a research paper on a idea Patch Classifier of Face Shape Outline Using Gray-Value Variance with Bilinear Interpolation
[{"from": "human", "value": "I am writing a research paper on a idea Patch Classifier of Face Shape Outline Using Gray-Value Variance with Bilinear Interpolation"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  proposes a method to classify whether a landmark, which consists of the outline in a face shape model in the shape model based approaches, is properly fitted to feature points. Through this method, the reliability of information can be determined in the process of managing and using the shape. The enlarged face image by image sensor is processed by bilinear interpolation.  use the gray-value variance that considers the texture feature of skin for classification of landmarks. The gray-value variance is calculated in skin area of the patch constructed around the landmark. In order to make a system strong to poses,  project the image of face to the frontal face shape model. And, to fill out each area, the area with insufficient pixel information is filled out with bilinear interpolation. When the fitting is properly done, it has the variance with a low value to be calculated for smooth skin texture. On the other hand, the variance for misaligned landmark shows a high variance by the background and facial contour gradient.  have proposed a classifier using this characteristic and, as a result, classified the true and false in the landmark with an accuracy of 83.32% through the patch classifier."}]