Fusion of appearance image and passive stereo depth map for face recognition based on the bilateral 2DLDA

Authors:
Jian-Gang Wang;Hui Kong;Eric Sung;Wei-Yun Yau;Eam Khwang Teoh
Affiliations:
Institute for Infocomm Research, Singapore;School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore;School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore;Institute for Infocomm Research, Singapore;School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore
Venue:
Journal on Image and Video Processing
Year:
2007

Citing 22
Cited 2

Labeling of human face components from range data

CVGIP: Image Understanding
Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection

IEEE Transactions on Pattern Analysis and Machine Intelligence
On Combining Classifiers

IEEE Transactions on Pattern Analysis and Machine Intelligence
A morphable model for the synthesis of 3D faces

Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Frontal-view face detection and facial features extraction using color and morphological operations

Pattern Recognition Letters
The FERET Evaluation Methodology for Face-Recognition Algorithms

IEEE Transactions on Pattern Analysis and Machine Intelligence
Face verification from 3D and grey level clues

Pattern Recognition Letters
Person Identification Using Multiple Cues

IEEE Transactions on Pattern Analysis and Machine Intelligence
Use of depth and colour eigenfaces for face recognition

Pattern Recognition Letters
3D Human Face Recognition Using Point Signature

FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
A subdivision algorithm for computer display of curved surfaces.

A subdivision algorithm for computer display of curved surfaces.
Face Recognition Based on Fitting a 3D Morphable Model

IEEE Transactions on Pattern Analysis and Machine Intelligence
Face recognition with visible and thermal infrared imagery

Computer Vision and Image Understanding - Special issue on Face recognition
Two-Dimensional PCA: A New Approach to Appearance-Based Face Representation and Recognition

IEEE Transactions on Pattern Analysis and Machine Intelligence
Face recognition: A literature survey

ACM Computing Surveys (CSUR)
Deformation Analysis for 3D Face Matching

WACV-MOTION '05 Proceedings of the Seventh IEEE Workshops on Application of Computer Vision (WACV/MOTION'05) - Volume 1 - Volume 01
An Evaluation of Multimodal 2D+3D Face Biometrics

IEEE Transactions on Pattern Analysis and Machine Intelligence
A Framework of 2D Fisher Discriminant Analysis: Application to Face Recognition with Small Number of Training Samples

CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
A survey of approaches and challenges in 3D and multi-modal 3D + 2D face recognition

Computer Vision and Image Understanding
Rapid and brief communication: Two-dimensional discriminant transform for face recognition

Pattern Recognition
Multi-biometrics using facial appearance, shape and temperature

FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Fusion of appearance and depth information for face recognition

AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication

Incremental two-dimensional linear discriminant analysis with applications to face recognition

Journal of Network and Computer Applications
Rapid stereo-vision enhanced face detection

ICIP'09 Proceedings of the 16th IEEE international conference on Image processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a novel approach for face recognition based on the fusion of the appearance and depth information at the match score level. We apply passive stereoscopy instead of active range scanning as popularly used by others. We show that present-day passive stereoscopy, though less robust and accurate, does make positive contribution to face recognition. By combining the appearance and disparity in a linear fashion, we verified experimentally that the combined results are noticeably better than those for each individual modality. We also propose an original learning method, the bilateral two-dimensional linear discriminant analysis (B2DLDA), to extract facial features of the appearance and disparity images. We compare B2DLDA with some existing 2DLDA methods on both XM2VTS database and our database. The results show that the B2DLDA can achieve better results than others.