Face recognition using standard 2D images struggles to cope with changes in illumination and pose. 3D face recognition algorithms have been more successful in dealing with these challenges. 3D face shape data is used as an independent cue for face recognition and has also been combined with texture to facilitate multimodal face recognition. Additionally, 3D face models have been used for pose c...

In this paper, a noble nonintrusive three-dimensional (3D) face modeling system for random-profile-based 3D face recognition is presented. Although recent two-dimensional (2D) face recognition systems can achieve a reliable recognition rate under certain conditions, their performance is limited by internal and external changes, such as illumination and pose variation. To address these issues, 3...

This paper proposes a three-dimensional (3D) face recognition system using passive stereo vision. So far, the reported 3D face recognition techniques have used active 3D measurement methods to capture high-quality 3D facial information. However, active methods employ structured illumination (structure projection, phase shift, moire topography, etc.) or laser scanning, which is not desirable in ...

Many researches in face recognition have been dealing with the challenge of the great variability in head pose, lighting intensity and direction,facial expression, and aging. The main purpose of this overview is to describe the recent 3D face recognition algorithms. The last few years more and more 2D face recognition algorithms are improved and tested on less than perfect images. However, 3D m...

Deep networks trained on millions of facial images are believed to be closely approaching human-level performance in face recognition. However, open world face recognition still remains a challenge. Although, 3D face recognition has an inherent edge over its 2D counterpart, it has not benefited from the recent developments in deep learning due to the unavailability of large training as well as ...

Three Dimensional (3D) human face recognition is emerging as a significant biometric technology. Research interest into 3D face recognition has increased during recent years due to availability of improved 3D acquisition devices and processing algorithms. A 3D face image is represented by 3D meshes or range images which contain depth information. Range images have several advantages over 2D int...

The ability to model 3D objects from monocular video allows for a number of very useful applications, for instance: 3D face recognition, fast prototyping and entertainment. At present there are a number of methods available for 3D modelling from this and similar data. However many of them are either not robust when presented with real world data, or tend to bias their results to a prior model. ...

Biometric measurements received an increasing interest for security applications in the last two decades. After the 911 terrorist attacks, face recognition has been an active research in this area. However, very few research group focus on face recognition from both 2D and 3D facial images. Almost all existing recognition systems rely on a single type of face information: 2D intensity (or color...

Automated human face recognition is required in numerous applications. While considerable progress has been made in color/two dimensional (2D) face recognition, three dimensional (3D) face recognition technology is much less developed. 3D face recognition approaches based on the appearance of range images and geometric properties of the facial surface have been proposed. Methods that combine 2D...