[1]RUAN Xiaohu,LI Weijun,QIN Hong,et al.An assessment method for face alignment based on feature matching[J].CAAI Transactions on Intelligent Systems,2015,10(1):12-19.[doi:10.3969/j.issn.1673-4785.201312064]
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An assessment method for face alignment based on feature matching
CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
10
Number of periods:
2015 1
Page number:
12-19
Column:
学术论文—机器感知与模式识别
Public date:
2015-03-25
- Title:
- An assessment method for face alignment based on feature matching
- Keywords:
- face recognition; image normalization; alignment assessment; image feature; SIFT descriptor; gradient orientation histogram; key point location; image matching
- CLC:
- TP183
- DOI:
- 10.3969/j.issn.1673-4785.201312064
- Abstract:
- The lacking of confirmation for face alignment leads to an incorrect feature match. The decline of recognition rate in current application of face recognition is called "mis-alignment crash". Therefore, it is necessary to test and filter the normalized face images to make sure only the aligned face images can go through the recognition procedure. In the method, a bunch of right-alignment normalized face images were used to form a mean face which was defined as the standard face. The key points location theory of SIFT was used to get the key points of standard face and the features of neighboring images were extracted on the basis of blocked statistical histogram in gradient orientation. The location of key points of a standard face was taken as the positioning point of a face to be detected. Using the same method to extract the features of neighboring images showed that the similarities of the test images to the standard face were calculated according to their corresponding feature descriptors of the key points. A reasonable threshold was chosen to estimate and classify the images according to their similarities to standard face. The experiment proved that this method is effective in eliminating mis-aligned face image effectively and is beneficial for increasing the reliability of a face recognition system.
- References:
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Last Update:
2015-06-16