Region-based super-resolution aided facial feature extraction from low-resolution video sequences

Loading...
Thumbnail Image

Date

Journal Title

Journal ISSN

Volume Title

Publisher

Access Rights

info:eu-repo/semantics/closedAccess

Abstract

Facial feature extraction is a fundamental problem in image processing. Correct extraction of features is essential for the success of many applications. Typical feature extraction algorithms fail for low resolution images which do not contain sufficient facial detail. In this paper, a region-based super-resolution aided facial feature extraction method for low resolution video sequences is described. The region based approach makes use of segmented faces as the region of interest whereby a significant reduction in computational burden of the super-resolution algorithm is achieved. The results indicate that the region-based super-resolution aided extraction algorithm provides significant performance improvement in terms of correct detection in accurately locating the facial feature points. © 2005 IEEE.

Description

2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 --

Keywords

Facial feature extraction, Feature extraction algorithms, Low resolution images, Super resolution, Algorithms, Computational complexity, Feature extraction, Image analysis, Object recognition, Optical resolving power, Video signal processing, Face recognition

Journal or Series

Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing

WoS Q Value

Scopus Q Value

Volume

II

Issue

Citation

Endorsement

Review

Supplemented By

Referenced By