• Corpus ID: 38053204

griffith . edu . au Face Recognition across Pose : A Review

  title={griffith . edu . au Face Recognition across Pose : A Review},
  author={Xiaozheng Zhang and Yongsheng Gao},



Pose-robust face recognition using geometry assisted probabilistic modeling

  • Xiaoming LiuTsuhan Chen
  • Computer Science
    2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05)
  • 2005
A geometry assisted probabilistic approach to improve face recognition under pose variation by approximate a human head with a 3D ellipsoid model, which enables the recognition to be conducted by comparing the texture maps instead of the original images, as done in traditional face recognition.

Face recognition: a convolutional neural-network approach

A hybrid neural-network for human face recognition which compares favourably with other methods and analyzes the computational complexity and discusses how new classes could be added to the trained recognizer.

The CMU Pose, Illumination, and Expression Database

In the Fall of 2000, we collected a database of more than 40,000 facial images of 68 people. Using the Carnegie Mellon University 3D Room, we imaged each person across 13 different poses, under 43

Face recognition/detection by probabilistic decision-based neural network

The paper demonstrates a successful application of PDBNN to face recognition applications on two public (FERET and ORL) and one in-house (SCR) databases and experimental results on three different databases such as recognition accuracies as well as false rejection and false acceptance rates are elaborated.

Combination of Warping Robust Elastic Graph Matching and Kernel-Based Projection Discriminant Analysis for Face Recognition

A robust face recognition algorithm based on the elastic graph matching (EGM) and discriminative feature analysis algorithm is proposed, which outperformed the compared approaches and compared the performance with recently developed approaches.

Toward Pose-Invariant 2-D Face Recognition Through Point Distribution Models and Facial Symmetry

This paper proposes novel ways to deal with pose variations in a 2-D face recognition scenario and shows that if only pose parameters are modified, client specific information remains in the warped image and discrimination between subjects is more reliable.

Locally Linear Regression for Pose-Invariant Face Recognition

A simple, but efficient, novel locally linear regression (LLR) method, which generates the virtual frontal view from a given nonfrontal face image, and shows distinct advantage of the proposed method over Eigen light-field method.

Synthesis of Novel Views from a Single Face Image

  • T. Vetter
  • Computer Science, Art
    International Journal of Computer Vision
  • 2004
A new technique is described for synthesizing images of faces from new viewpoints, when only a single 2D image is available, which is interesting for view independent face recognition tasks as well as for image synthesis problems in areas like teleconferencing and virtualized reality.

Using Stereo Matching for 2-D Face Recognition Across Pose

This work built a face recognition system on top of a dynamic programming stereo matching algorithm and showed that the method works well even when the epipolar lines the authors use do not exactly fit the viewpoints.