Face Recognition using Shading-Based Curvature Attributes

Authors:
Yang Li;Edwin R. Hancock
Affiliations:
University of York, UK;University of York, UK
Venue:
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Year:
2004

Citing 0
Cited 4

Coronal loop detection from solar images

Pattern Recognition
Face recognition with irregular region spin images

SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
Scale-space approach for the comparison of HK and SC curvature descriptions as applied to object recognition

ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Transform based face recognition with partial and full feature vector using DCT and Walsh transform

Proceedings of the International Conference & Workshop on Emerging Trends in Technology

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper we apply shape-from-shading to face images to extract elds of surface normals and make estimates of surface curvature attributes. The attributes studied include minimum andmaximum curvature, mean and Gaussian curvature, and, curvedness and shape-index. The curvature attributes are encoded as histograms and are used to perform recognition using a number of distance and similarity measures including the Euclidean distance, the Shannon entropy, the Renyi entropy and the Tsallis entropy. We compare the results obtained using the differentcurvature attributes and the different entropy measures. Using precision-recallcurves, we find that the best performance is delivered when the Shannonentropy is applied to histograms of shape index and curvedness.