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

نویسندگان

  • Raymond S. Smith
  • Terry Windeatt
چکیده

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.

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تاریخ انتشار 2010