We introduce a novel methodology applicable to face matching and fast screening of large facial databases. The proposed shape comparison method operates on edge maps and derives holistic similarity measures, yet, it does not require solving the point correspondence problem. While the use of edge ima
β¦ LIBER β¦
Gray Hausdorff distance measure for comparing face images
β Scribed by Vivek, E.P.; Sudha, N.
- Book ID
- 114627558
- Publisher
- IEEE
- Year
- 2006
- Tongue
- English
- Weight
- 850 KB
- Volume
- 1
- Category
- Article
- ISSN
- 1556-6013
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
COMPARING FACE IMAGES USING THE MODIFIED
β
BARNABΓS TAKΓCS
π
Article
π
1998
π
Elsevier Science
π
English
β 492 KB
Efficiently comparing face images using
β
Gao, Y.
π
Article
π
2003
π
The Institution of Electrical Engineers
π
English
β 355 KB
Robust Hausdorff distance measure for fa
β
Vivek E. P; N. Sudha
π
Article
π
2007
π
Elsevier Science
π
English
β 612 KB
A novel weighted Hausdorff distance for
β
Huachun Tan; Yu-Jin Zhang
π
Article
π
2006
π
Elsevier Science
π
English
β 263 KB
A new Hausdorff distance for image match
β
Chunjiang Zhao; Wenkang Shi; Yong Deng
π
Article
π
2005
π
Elsevier Science
π
English
β 266 KB
Spatially eigen-weighted Hausdorff dista
β
Kwan-Ho Lin; Kin-Man Lam; Wan-Chi Siu
π
Article
π
2003
π
Elsevier Science
π
English
β 325 KB
Hausdor distance is an e cient measure of the similarity of two point sets. In this paper, we propose a new spatially weighted Hausdor distance measure for human face recognition. The weighting function used in the Hausdor distance measure is based on an eigenface, which has a large value at locatio