Face recognition from 2D and 3D images using structural Hausdorff distance

Author(s):  
Yingjie Wang ◽  
Chin-Seng Chua ◽  
Yeong-Khing Ho
2005 ◽  
Vol 23 (11) ◽  
pp. 1018-1028 ◽  
Author(s):  
Yingjie Wang ◽  
Chin-Seng Chua

2002 ◽  
Vol 23 (10) ◽  
pp. 1191-1202 ◽  
Author(s):  
Yingjie Wang ◽  
Chin-Seng Chua ◽  
Yeong-Khing Ho

2013 ◽  
Vol 311 ◽  
pp. 173-178
Author(s):  
Jia Shing Sheu ◽  
Ho Nien Shou ◽  
Li Peng Wang ◽  
Tsong Liang Huang

Biometric is used to confirm the unique of identity. In general, face is the most characteristic to recognize a person. In this paper, it is emphasized and compared the quality of 2D and 3D face recognition. There are three parts in this paper. First part is the detection of skin color which is used RGB color space. In order to reduce color red and green which are sensitive to illuminant, Normalized Color Coordinate (NCC) method is chosen to pick up the range of skin color directly. Second, to increase choosing of the important characteristics by Principle Component Analysis (PCA) the wavelength distinguishes technique is used to make 3D images. The third part is about identifying. An improved PCA through a transfer matrix to get optimal total scatter matrix of within-class scatter matrix is used. The optimal total scatter matrix represents the eigenvalue of face characteristics. Finally, the recognition rate and process performance between 2D and 3D images are compared via Euclidean Distance. The efficiency and recognition rate of 3D images are superior to 2D images. The recognition rate of 3D images attains to 92% and costs 0.39 second to recognize each image. It is improved 28% compared with the recognition rate of 2D images.


2021 ◽  
Vol 7 (3) ◽  
pp. 209-219
Author(s):  
Iris J Holzleitner ◽  
Alex L Jones ◽  
Kieran J O’Shea ◽  
Rachel Cassar ◽  
Vanessa Fasolt ◽  
...  

Abstract Objectives A large literature exists investigating the extent to which physical characteristics (e.g., strength, weight, and height) can be accurately assessed from face images. While most of these studies have employed two-dimensional (2D) face images as stimuli, some recent studies have used three-dimensional (3D) face images because they may contain cues not visible in 2D face images. As equipment required for 3D face images is considerably more expensive than that required for 2D face images, we here investigated how perceptual ratings of physical characteristics from 2D and 3D face images compare. Methods We tested whether 3D face images capture cues of strength, weight, and height better than 2D face images do by directly comparing the accuracy of strength, weight, and height ratings of 182 2D and 3D face images taken simultaneously. Strength, height and weight were rated by 66, 59 and 52 raters respectively, who viewed both 2D and 3D images. Results In line with previous studies, we found that weight and height can be judged somewhat accurately from faces; contrary to previous research, we found that people were relatively inaccurate at assessing strength. We found no evidence that physical characteristics could be judged more accurately from 3D than 2D images. Conclusion Our results suggest physical characteristics are perceived with similar accuracy from 2D and 3D face images. They also suggest that the substantial costs associated with collecting 3D face scans may not be justified for research on the accuracy of facial judgments of physical characteristics.


Author(s):  
M. Yamni ◽  
A. Daoui ◽  
O. El ogri ◽  
H. Karmouni ◽  
M. Sayyouri ◽  
...  

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