3D Face Recognition is an active area of research for past several years. For a 3D face recognition system one would like to have an accurate as well as low cost setup for constructing 3D face model. In this paper, we use Profilometry approach to obtain a 3D face model. This method gives a low cost solution to the problem of acquiring 3D data and the 3D face models generated by this method are ...

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...

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...

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. ...

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...

Although a lot of promising research findings have been studied on 3D face modeling in the past years, it is still a challenge to generate realistic 3D human face models and facial animations. This paper presents a novel approach to model 3D faces automatically from still images or video sequences without manual interactions. Our proposed scheme comprises three steps. First, we offline construc...

3D face dense tracking aims to find dense inter-frame correspondences in a sequence of 3D face scans and constitutes a powerful tool for many face analysis tasks, e.g., 3D dynamic facial expression analysis. The majority of the existing methods just fit a 3D face surface or model to a 3D target surface without considering temporal information between frames. In this paper, we propose a novel me...

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 ...

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 ...