Face expression automatic identification method
A facial expression, automatic recognition technology, applied in character and pattern recognition, image data processing, instruments, etc., can solve the problems of poor light noise robustness, insufficient local information extraction, long calculation time, etc.
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Embodiment 1
[0119] This embodiment is a method for automatic recognition of facial expressions based on irregular segmentation of facial feature parts and multi-feature fusion. The specific steps are as follows:
[0120] The first step, facial expression image preprocessing:
[0121] Using the following formula (1), the facial expression image collected from the USB interface of the computer is converted from the RGB space to the gray space, and then the size of the image is normalized to obtain the facial expression gray image I gray ,
[0122] I gray =0.299R+0.587G+0.114B (1),
[0123] In formula (1), R, G and B are the components of the red, green and blue channels respectively,
[0124] This completes the facial expression image preprocessing;
[0125] The second step is to automatically locate and mark the key feature points of the facial expression image:
[0126] Use the AAM algorithm to process the facial expression grayscale image I obtained in the first step above. gray Ac...
Embodiment 2
[0210] This embodiment is an experimental verification of a facial expression automatic recognition method based on irregular segmentation of facial feature parts and multi-feature fusion adopted in the present invention.
[0211] In this embodiment, experiments have been carried out on the JAFFE facial expression database and the CK+ facial expression database. Among them, the JAFFE database has a total of 213 facial expression images, which are composed of seven facial expressions of ten women, including neutrality, happiness, sadness, anger, surprise, fear and disgust. 137 facial expression images in the JAFFE database are selected as training data, and the remaining 76 facial expression images are used for testing. The CK+ facial expression database contains 123 participants from different countries and regions, and a total of 593 facial expression sequences. Each facial expression sequence starts with a neutral facial expression and ends with a peak frame of facial expres...
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