Consensus and stacking based fusion and survey of facial feature point detectors

Author(s):  
Sezer Ulukaya ◽  
Esra Nur Sandıkçı ◽  
Çiğdem Eroğlu Erdem
Keyword(s):  
Author(s):  
Masahiko Minamoto ◽  
Hidaka Sato ◽  
Takahiro Kanno ◽  
Tetsuro Miyazaki ◽  
Toshihiro Kawase ◽  
...  

2015 ◽  
Vol 2015 ◽  
pp. 1-6
Author(s):  
Hong-an Li ◽  
Yongxin Zhang ◽  
Zhanli Li ◽  
Huilin Li

It is an important task to locate facial feature points due to the widespread application of 3D human face models in medical fields. In this paper, we propose a 3D facial feature point localization method that combines the relative angle histograms with multiscale constraints. Firstly, the relative angle histogram of each vertex in a 3D point distribution model is calculated; then the cluster set of the facial feature points is determined using the cluster algorithm. Finally, the feature points are located precisely according to multiscale integral features. The experimental results show that the feature point localization accuracy of this algorithm is better than that of the localization method using the relative angle histograms.


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