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Feature selection of facial displays for detection of non verbal communication in natural conversation

Sheerman-Chase, T, Ong, E-J and Bowden, R (2009) Feature selection of facial displays for detection of non verbal communication in natural conversation In: ICCV 2009, 2009-09-27 - 2009-10-04, Kyoto, Japan.

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Recognition of human communication has previously focused on deliberately acted emotions or in structured or artificial social contexts. This makes the result hard to apply to realistic social situations. This paper describes the recording of spontaneous human communication in a specific and common social situation: conversation between two people. The clips are then annotated by multiple observers to reduce individual variations in interpretation of social signals. Temporal and static features are generated from tracking using heuristic and algorithmic methods. Optimal features for classifying examples of spontaneous communication signals are then extracted by AdaBoost. The performance of the boosted classifier is comparable to human performance for some communication signals, even on this challenging and realistic data set.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing
Authors :
Sheerman-Chase, T
Ong, E-J
Bowden, R
Date : 2009
DOI : 10.1109/ICCVW.2009.5457525
Contributors :
Additional Information : Copyright 2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Depositing User : Symplectic Elements
Date Deposited : 22 May 2012 14:27
Last Modified : 31 Oct 2017 14:33

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