Abstract
We present a new noninvasive multi-sensor capturing system for recording video, sound and motion data. The characteristic of the system is its 1msec. order accuracy hardware level synchronization among all the sensors as well as automatic extraction of variety of ground truth from the data. The proposed system enables the analysis of the correlation between variety of psychophysiological model (modalities), such as facial expression, body temperature changes, gaze analysis etc... . Following benchmarks driven framework principles, the data captured by our system is used to establish benchmarks for evaluation of the algorithms involved in the automatic emotions recognition process.
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Polikovsky, S., Quiros-Ramirez, M.A., Onisawa, T., Kameda, Y., Ohta, Y. (2013). A Non-invasive Multi-sensor Capturing System for Human Physiological and Behavioral Responses Analysis. In: Schwenker, F., Scherer, S., Morency, LP. (eds) Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction. MPRSS 2012. Lecture Notes in Computer Science(), vol 7742. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37081-6_8
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DOI: https://doi.org/10.1007/978-3-642-37081-6_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-37080-9
Online ISBN: 978-3-642-37081-6
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