Datasets and code

DEAP Dataset

A multimodal dataset for the analysis of human affective states. The electroencephalogram (EEG) and peripheral physiological signals of 32 participants were recorded as each watched 40 one-minute long excerpts of music videos.

Amigos Dataset

A dataset for research on affect, personality traits and mood by means of neuro-physiological signals. We elicited affect using both short and long videos in two configurations, one with individual viewers and one with groups of viewers. Electroencephalogram (EEG), Electrocardiogram (ECG), and Galvanic Skin Response (GSR), were recorded using wearable sensors.

Code

Diclaimer: We provide code and/or executable for academic and research purposes in an 'as-is' basis and without any warranties of their correctness. Please, refer to the relevant papers if you use the code in any academic publication, and inform us (i.patras@eecs.qmul.ac.uk) or the first author if you have any suggestions.

Support Tucker Machines. This code implements Support Tucker Machines (STuMs) and Sw-STuMs, as presented in Irene Kotsia and Ioannis Patras, "Support Tucker Machines", in CVPR 2011, 2011. pdf, bibtex
Tensor Regression. This code implements Support Tensor Regression (STR) as presented in Weiwei Guo, Irene Kotsia and Ioannis Patras, "Tensor Learning for Regression", in IEEE Transactions on Image Processing, accepted for publication, 2011. bibtex
Max-Margin Semi-NMF. This code implements the paper Max-Margin Semi-NMF (MNMF) as presented in Vijay Kumar, Irene Kotsia and Ioannis Patras, "Max-Margin Semi-NMF", in BMVC 2011. pdf, bibtex

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