NDLI: Recognizing facial expressions using novel motion based features

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Recognizing facial expressions using novel motion based features

Content Provider	ACM Digital Library
Author	Vamshi, Bandla Mukherjee, Snehasis Harish, S. V. S. Krishna, Repala Vamshi Reddy, K. V. Sai Vineeth Kumar
Abstract	This paper introduces two novel motion based features for recognizing human facial expressions. The proposed motion features are applied for recognizing facial expressions from a video sequence. The proposed bag-of-words based scheme represents each frame of a video sequence as a vector depicting local motion patterns during a facial expression. The local motion patterns are captured by an efficient derivation from optical flow. Motion features are clustered and stored as words in a dictionary. We further generate a reduced dictionary by ranking the words based on some ambiguity measure. We prune out the ambiguous words and continue with key words in the reduced dictionary. The ambiguity measure is given by applying a graph-based technique, where each word is represented as a node in the graph. Ambiguity measures are obtained by modelling the frequency of occurrence of the word during the expression. We form expression descriptors for each expression from the reduced dictionary, by applying an efficient kernel. The training of the expression descriptors are made following an adaptive learning technique. We tested the proposed approach with standard dataset. The proposed approach shows better accuracy compared to the state-of-the-art.
Starting Page	1
Ending Page	8
Page Count	8
File Format	PDF
ISBN	9781450347532
DOI	10.1145/3009977.3010004
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-12-18
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Adaptive learning Gwof Facial expression Optical flow Wof
Content Type	Text
Resource Type	Article

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