@inproceedings{14654cb428274668a198d567fa2b2891,
title = "Y{\"u}z nirengi noktalarinin zamansal {\"o}z-benzerliǧine ve kelime {\c c}antasina dayali y{\"u}z {\.i}fadesi ve kafa hareketi tanima",
abstract = "Automatic recognition of facial expressions and head gestures plays an important role in a wide range of research area including sign language recognition and human-computer interaction. In this work, we adopt the well-performing self-similarity based action recognition method to classify facial expressions and head gestures. Additionally, we propose a novel approach for facial gesture recognition based on the histogram of tracked facial landmarks. We fuse the presented techniques with our previous Hidden Markov Model based approach [1] and get 15% increase in classification results.",
author = "Ismail Ari and Hua Gao and Ekenel, {Hazim K.} and Lale Akarun",
year = "2010",
doi = "10.1109/SIU.2010.5653965",
language = "T{\"u}rk{\c c}e",
isbn = "9781424496716",
series = "SIU 2010 - IEEE 18th Signal Processing and Communications Applications Conference",
pages = "836--839",
booktitle = "SIU 2010 - IEEE 18th Signal Processing and Communications Applications Conference",
note = "18th IEEE Signal Processing and Communications Applications Conference, SIU 2010 ; Conference date: 22-04-2010 Through 24-04-2010",
}