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Facial Expression Detection using Filtered Local Binary Pattern Features with ECOC Classifiers and Platt Scaling

Smith, RS and Windeatt, T (2010) Facial Expression Detection using Filtered Local Binary Pattern Features with ECOC Classifiers and Platt Scaling In: Workshop on Applications of Pattern Analysis, 2010-08-31 - 2010-09-02, Windsor, England.

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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 filtering (FCBF). Secondly we show how Platt scaling can be used to improve the performance of an error-correcting output code (ECOC) classifier.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Authors :
NameEmailORCID
Smith, RSraymond.smith@surrey.ac.ukUNSPECIFIED
Windeatt, Tt.windeatt@surrey.ac.ukUNSPECIFIED
Date : 2010
Depositing User : Symplectic Elements
Date Deposited : 17 May 2017 11:41
Last Modified : 17 May 2017 14:58
URI: http://epubs.surrey.ac.uk/id/eprint/832317

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