A quantitative evaluation for 3D face reconstruction algorithms

3D facial reconstruction is an emerging and interesting application in the field of computer graphics and computer vision. It is difficult and challenging to reconstruct the 3D facial model from a single photo because of arbitrary poses, non-uniform illumination, expressions, and occlusions. Detailed 3D facial models are difficult to reconstruct because every algorithm has some limitations related to profile view, fine detail, accuracy, and speed. The major problem is to develop 3D face with texture of large poses, wild faces, large training data, and occluded faces. Mostly algorithms use convolution neural networks and deep learning frameworks to create facial model. 3D face reconstruction algorithms used for application such as 3D printing, 3D VR games and facial recognition. Different issues, problems and their proposed solutions are discussed. Different facial dataset and facial 3DMM used for 3D face reconstructing from a single photo are explained. The recent state of art 3D facial reconstruction and 3D face learning methods developed in 2019 is briefly explained.

Download Full-text

IMAGE BASED 3D FACE RECONSTRUCTION: A SURVEY

International Journal of Image and Graphics ◽

10.1142/s0219467809003411 ◽

2009 ◽

Vol 09 (02) ◽

pp. 217-250 ◽

Cited By ~ 15

Author(s):

GEORGIOS STYLIANOU ◽

ANDREAS LANITIS

Keyword(s):

3D Reconstruction ◽

Feature Detection ◽

Low Cost ◽

Reconstruction Algorithms ◽

3D Face Reconstruction ◽

Reconstruction Process ◽

3D Face ◽

Advantages And Disadvantages ◽

Face Reconstruction ◽

Reconstruction Methods

The use of 3D data in face image processing applications has received considerable attention during the last few years. A major issue for the implementation of 3D face processing systems is the accurate and real time acquisition of 3D faces using low cost equipment. In this paper we provide a survey of 3D reconstruction methods used for generating the 3D appearance of a face using either a single or multiple 2D images captured with ordinary equipment such as digital cameras and camcorders. In this context we discuss various issues pertaining to the general problem of 3D face reconstruction such as the existence of suitable 3D face databases, correspondence of 3D faces, feature detection, deformable 3D models and typical assumptions used during the reconstruction process. Different approaches to the problem of 3D reconstruction are presented and for each category the most important advantages and disadvantages are outlined. In particular we describe example-based methods, stereo methods, video-based methods and silhouette-based methods. The issue of performance evaluation of 3D face reconstruction algorithms, the state of the art and future trends are also discussed.

Download Full-text