PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Facial Expression Detection using Filtered Local Binary Pattern Features with ECOC Classifiers and Platt Scaling.
r s smith and Terry Windeatt
JMLR Volume track 11, pp. 111-118, 2011.

Abstract

We outline a design for a FACS-based facial expression recognition system and describe in more detail the implementation of two of its main components. Firstly we look at how features that are useful from a pattern analysis point of view can be extracted from a raw input image. We show that good results can be obtained by using the method of local binary patterns (LPB) to generate a large number of candidate features and then selecting from them using fast correlation-based ltering (FCBF). Secondly we show how Platt scaling can be used to improve the performance of an error-correcting output code (ECOC) classi er.

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:9151
Deposited By:Terry Windeatt
Deposited On:21 February 2012