吉林大学学报(工学版) ›› 2015, Vol. 45 ›› Issue (2): 606-612.doi: 10.13229/j.cnki.jdxbgxb201502040

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Facial feature tracking based on mind evolutionary algorithm

LI Gen,LI Wen-hui   

  1. College of Computer Science and Technology, Jilin University, Changchun 130012, China
  • Received:2013-11-22 Online:2015-04-01 Published:2015-04-01

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Abstract:

A new facial feature point tracking method based on Mind Evolutionary Algorithm (MEA) was presented. The integrated feature model was formed by Scale Invariant Feature Transform (SIFT) feature in tracking region. Then the feature points were determined. The existing region of the feature points were restricted by the space distribution of the integrated feature model. The MEA was used to compute the best-case coverage solution by similartaxis procedure and dissimilation procedure in target frames. It can more precisely determine the restriction region of tracking feature points, and improve tracking precision and efficiency. The original feature and replaced feature were introduced to make the tracking steadier and faster in complicated condition. The experiment results indicate that the new method can stably track 95% feature points in complicated condition, while the tracking speed can be kept withing 25 frames per second.

Key words: computer application, mind evolutionary algorithm (MEA), SIFT feature, feature point tracking, feature point restriction

CLC Number: 

  • TP391
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