Improvement for 3D Coordinate Reconstruction of Facial Feature Points in Video Sequences

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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A system for the automatic extraction of 3-D facial feature points for face model calibration

10.1109/icip.2000.899279 ◽

2000 ◽

Author(s):

Yong Yan ◽

K. Challapali

Keyword(s):

Model Calibration ◽

Facial Feature ◽

Automatic Extraction ◽

Feature Points ◽

Face Model

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Robust facial feature points extraction in color images

Engineering Applications of Artificial Intelligence ◽

10.1016/j.engappai.2010.09.001 ◽

2011 ◽

Vol 24 (1) ◽

pp. 195-200 ◽

Cited By ~ 2

Author(s):

Yue Zhou ◽

Yin Li ◽

Zheng Wu ◽

Meilin Ge

Keyword(s):

Facial Feature ◽

Color Images ◽

Feature Points

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LOCAL LAPLACIAN DETAIL LEARNING FOR FACE AGING MANIPULATION

International Journal of Image and Graphics ◽

10.1142/s0219467807002775 ◽

2007 ◽

Vol 07 (03) ◽

pp. 463-480

Author(s):

MINGLI SONG ◽

HUIQIONG WANG ◽

CHUN CHEN

Keyword(s):

Computer Animation ◽

Skin Color ◽

Aging Process ◽

Facial Feature ◽

Skin Aging ◽

Differential Method ◽

Feature Points ◽

Hair Style ◽

Face Aging ◽

Local Image

Face aging is a challenging work in image processing and computer animation field. In this paper, a novel local image Laplacian differential method is proposed to learn this complex face transformation. Firstly, together with the facial feature points correspondence, we extract the aging facial details from example face and apply to the target one by a global and a local Laplacian skin aging model respectively, and the latter makes the results more realistic in our experiment. Then, the skin color and hair style adjustments are carried out to simulate the aging process completely, making the results look more competitive and natural. Our experiment shows that our method is robust and appreciable.

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