Compact multi-level representation of human faces for identification
Compact multi-level representation of human faces for identification
- Author(s): M.A. Grudin ; P.J.G. Lisboa ; D.M. Harvey
- DOI: 10.1049/cp:19970865
For access to this article, please select a purchase option:
Buy conference paper PDF
Buy Knowledge Pack
IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.
6th International Conference on Image Processing and its Applications — Recommend this title to your library
Thank you
Your recommendation has been sent to your librarian.
- Author(s): M.A. Grudin ; P.J.G. Lisboa ; D.M. Harvey Source: 6th International Conference on Image Processing and its Applications, 1997 p. 111 – 115
- Conference: 6th International Conference on Image Processing and its Applications
- DOI: 10.1049/cp:19970865
- ISBN: 0 85296 692 X
- Location: Dublin, Ireland
- Conference date: 14-17 July 1997
- Format: PDF
In the last 15 years the task of face recognition has attracted considerable research attention. A number of advancements in automated face recognition use a variety of approaches. Although every technique has a particular merit, it is not yet possible to achieve fully reliable recognition, even in constrained environments. Specific problems that need to be solved are 3-D rotations, expression invariance, different appearances of the same person, integration of information from different scales, etc. The goal of this research is to solve the problem of integration of high-level information into a low-level representation of faces. Such integration results in a more efficient recognition performance. The subordinate advantage of this recognition scheme is a compact face representation, which reduces the database size and speeds up the recognition process.
Inspec keywords: image representation; face recognition; visual perception
Subjects: Computer vision and image processing techniques; Pattern recognition
Related content
content/conferences/10.1049/cp_19970865
pub_keyword,iet_inspecKeyword,pub_concept
6
6