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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/25093

Title: Camera-based Real-time Emotion Classification Using Support-Vector Machines
Authors: Swinkels, Wout
Claesen, Luc
Shen, Haibin
Issue Date: 2017
Citation: ICT.OPEN 2017: The Conference for ICT-Research in the Netherlands, Amersfoort, The Netherlands, 21-22/03/2017
Abstract: Extracting facial emotions is a great challenge in the area of computer vision, unlike humans, machines have a lot of difficulties with interpreting emotions. Due to the work of Viola-Jones [1] emotion detection is already more feasible. Using a fast algorithm to extract the region of interest (ROI) for emotion detection brings the development of a real-time emotion classification algorithm one step closer. In this research an emotion detection algorithm aimed at real-time implementation on an embedded platform has been developed. Several algorithms have been implemented and tested to evaluate their results with respect to their real-time performance potential and classification efficiency. The developed algorithm relies on three fundamental findings, which relate to the way humans interpret emotions.
URI: http://hdl.handle.net/1942/25093
ISBN: 9789492579027
Category: C2
Type: Conference Material
Appears in Collections: Research publications

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