scholarly journals An Automatic Landmark Localization Method for 2D and 3D Face

Author(s):  
Junquan Liu ◽  
Feipeng Da ◽  
Xing Deng ◽  
Yi Yu ◽  
Pu Zhang
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.


2014 ◽  
Vol 23 (12) ◽  
pp. 5108-5122 ◽  
Author(s):  
Mingli Song ◽  
Dacheng Tao ◽  
Shengpeng Sun ◽  
Chun Chen ◽  
Stephen J. Maybank

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Chenguang Shao

The target localization algorithm is critical in the field of wireless sensor networks (WSNs) and is widely used in many applications. In the conventional localization method, the location distribution of the anchor nodes is fixed and cannot be adjusted dynamically according to the deployment environment. The resulting localization accuracy is not high, and the localization algorithm is not applicable to three-dimensional (3D) conditions. Therefore, a Delaunay-triangulation-based WSN localization method, which can be adapted to two-dimensional (2D) and 3D conditions, was proposed. Based on the location of the target node, we searched for the triangle or tetrahedron surrounding the target node and designed the localization algorithm in stages to accurately calculate the coordinate value of the target. The relationship between the number of target nodes and the number of generated graphs was analysed through numerous experiments, and the proposed 2D localization algorithm was verified by extending it the 3D coordinate system. Experimental results revealed that the proposed algorithm can effectively improve the flexibility of the anchor node layout and target localization accuracy.


Author(s):  
Susana Mata ◽  
Cristina Conde ◽  
Araceli Sánchez ◽  
Enrique Cabello
Keyword(s):  
3D Face ◽  

2018 ◽  
Vol 7 (13) ◽  
pp. 119-139
Author(s):  
Zoran Lončarević ◽  
Muzafer Saračević ◽  
Muhedin Hadžić

2007 ◽  
Vol 28 (14) ◽  
pp. 1885-1906 ◽  
Author(s):  
Andrea F. Abate ◽  
Michele Nappi ◽  
Daniel Riccio ◽  
Gabriele Sabatino

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