Semantic access of frontal face images:: the expression-invariant problem

被引：4

作者：

Martínez, AM ^{[1
]}

机构：

[1] Purdue Univ, Sch Elect & Comp Engn, Robot Vis Lab, W Lafayette, IN 47906 USA

来源：

IEEE WORKSHOP ON CONTENT-BASED ACCESS OF IMAGE AND VIDEO LIBRARIES, PROCEEDINGS | 2000年

关键词：

D O I：

10.1109/IVL.2000.853840

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Semantic queries to a database of images are more desirable than lour-level feature queries, because they facilitate the user's task. One such approach is the object-related image retrieval. In the content efface images, it a's 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. The's paper presents a new local, probabilistic approach that accounts for this (Qs well as other previous studied) difficulty.

引用

页码：55 / 59

页数：5

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