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This is a Blog about Josh's 2011 Thesis at Usyd, others like it can be found here

Monday, 24 October 2011

Emotion detection in faces in an audience

Having seen the MIT Moodmeter, it seems like a better way to give feed back to a public speaker is by monitoring the audience. This will tell you if the speaker is really engaging the listeners which is really the prime measure of successful public speaking.

By recording the speak when monitoring the emotions of an audience, eg, happy or bored. you can inform the speaker where they started to lose the audience. The following articles concern emotion detection.

Affective Content Detection by Using Timing Features and Fuzzy Clustering
Min Xu, Suhuai Luo, and Jesse S. Jin

A robust multimodal approach for emotion recognition
Mingli Song Ã, Mingyu You, Na Li, Chun Chen

Emotion Recognition Based on Joint Visual and Audio Cues
Nicu Sebe, Ira Cohen, Theo Gevers, Thomas S. Huang

Neuro forge have a system they call synotive could be useful for emotion detection library.

I will have to decide if it will be feasible to use Kinect as i doubt it could fit more than 10 people in frame at a distance that its depth sensors will function. it may be nececary to use somthing different for or just restrict the project to work with small sample groups.

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