.png){kind=icon}
.png){kind=icon}
Return
Facial expression recognition using temporal POEM features
.png){kind=icon}
PRE
AI
DOI：10.1016/j.patrec.2017.08.008.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In this work, we propose a novel approach for Facial Expression Recognition (FER). We introduce the TPOEM (Temporal Patterns of Oriented Edge Magnitudes) features, which are volumetric extensions of the known POEM features by exploring adjacent frames and also temporal derivatives. To cope with the increase in the code length produced by TPOEM, we also present a novel coding scheme for the binary codes. TPOEM features are computed within non-overlapping image patches, and the final classification is achieved by combining the per-patch scores. The results showed increased accuracy compared to or better than state-of-the-art methods, while keeping the execution time low. (C) 2017 Elsevier B.V. All rights reserved.
Keywords:
Facial expression recognition
LBP
POEM
Pattern recognition
Feature extraction
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.3
Papers:
7.9K
Citations:
1.6W