@inproceedings{e69bb785878342eb96e70b5c7181f547,
title = "Emotion recognition using PHOG and LPQ features",
abstract = "We propose a method for automatic emotion recognition as part of the FERA 2011 competition. The system extracts pyramid of histogram of gradients (PHOG) and local phase quantisation (LPQ) features for encoding the shape and appearance information. For selecting the key frames, K-means clustering is applied to the normalised shape vectors derived from constraint local model (CLM) based face tracking on the image sequences. Shape vectors closest to the cluster centers are then used to extract the shape and appearance features. We demonstrate the results on the SSPNET GEMEP-FERA dataset. It comprises of both person specific and person independent partitions. For emotion classification we use support vector machine (SVM) and largest margin nearest neighbour (LMNN) and compare our results to the pre-computed FERA 2011 emotion challenge baseline.",
author = "Abhinav Dhall and Akshay Asthana and Roland Goecke and Tom Gedeon",
year = "2011",
month = jun,
day = "17",
doi = "10.1109/FG.2011.5771366",
language = "English",
isbn = "9781424491407",
series = "2011 IEEE International Conference on Automatic Face and Gesture Recognition and Workshops, FG 2011",
publisher = "IEEE, Institute of Electrical and Electronics Engineers",
pages = "878--883",
booktitle = "2011 IEEE International Conference on Automatic Face and Gesture Recognition and Workshops, FG 2011",
address = "United States of America",
note = "2011 IEEE International Conference on Automatic Face and Gesture Recognition and Workshops, FG 2011 ; Conference date: 21-03-2011 Through 25-03-2011",
}