Semantic Access of Frontal Face Images: The Expression-Invariant Problem

Authors:
Aleix M. Martínez
Affiliations:
-
Venue:
CBAIVL '00 Proceedings of the IEEE Workshop on Content-based Access of Image and Video Libraries (CBAIVL'00)
Year:
2000

Citing 0
Cited 2

Recognizing Imprecisely Localized, Partially Occluded, and Expression Variant Faces from a Single Sample per Class

IEEE Transactions on Pattern Analysis and Machine Intelligence
Facial asymmetry quantification for expression invariant human identification

Computer Vision and Image Understanding - Special issue on Face recognition

Quantified Score

Hi-index	0.00

Visualization

Abstract

Semantic queries to a database of images are more desirable than low-level feature queries, because they facilitate the user's task. One such approach is the object-related image retrieval. In the context of face images, it is of interest to retrieve images based on people's names and facial expressions. However, when images of the database are allowed to appear at different facial expressions, the face recognition approach encounters the expression-invariant problem, i.e. how to robustly identify a person's face for which its learning and testing face images differ in facial expression. This paper presents a new local, probabilistic approach that accounts for this (as well as other previous studied) difficulty.