吉林大学学报(工学版) ›› 2013, Vol. 43 ›› Issue (01): 186-191.

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Face detection under rotation in image plane based on scale invariant feature transform

LI Gen, LI Wen-hui   

  1. College of Computer Science and Technology, Jilin University, Changchun 130022, China
  • Received:2012-01-10 Online:2013-01-01 Published:2013-01-01

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Abstract: To solve the problem of face detection under rotation in image plane, an improved Scale Invariant Feature Transform (SIFT) algorithm is proposed. With the invariant properties of rotation, scale, translation and illustration, the SIFT algorithm is used to detect the rotation face in image plane. First, a pruning algorithm, combining the template and contrast, is used to increase the efficiency and filter the invalid key points; and a higher accuracy main direction algorithm is proposed. Then, the AdaBoost algorithm is used to train a common face classifier and compute the matching ratio of key points. Finally, the SIFT algorithm detects the face under rotation in image plane, and normalizes the face by the main direction of key points. Experiment results indicate that improved algorithm preserves the high detection ratio, and performs better in normalization precision and detection efficiency.

Key words: computer application, SIFT feature, Adaboost algorithm, face detection, face normalization

CLC Number: 

  • TP391
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