Work

Facial Expression Recognition using Encoded Dynamic Features

Year: 2007

Type: conference-paper

Abstract: In this paper, we propose a new approach of facial expression recognition. In order to capture the temporal characteristic of facial expressions, we design dynamic haar-like features to represent the facial images, and code them into binary patterns for the further analysis. Based on the encoded features, Adaboost is employed to learn the combination of optimal discriminant features to construct the classifier. The experiments carried on the CMU database show the promising performance of the proposed method.

Source: IEEE International Conference on Multimedia and Expo (ICME)

DOI: 10.1109/icme.2007.4284848

Authors: Peng Yang, Qingshan Liu, Dimitris N. Metaxas

Institutions: Rutgers, The State University of New Jersey, Chinese Academy of Sciences

Language: English

Topic: Face and Expression Recognition

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W2092946680

FWCI: 1.375

Cites: 31

Cited by: 33

Related to: 10