Reducing uncertainty in interval type-2 fuzzy sets for qualitative improvement in emotion recognition from facial expressions

The essence of the paper is to reduce uncertainty in interval type-2 fuzzy sets, and demonstrate the merit of uncertainty reduction in pattern classification problem. The area under the footprint of uncertainty has been used as the measure of uncertainty. A mathematical approach to reduce the area u...

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Bibliographic Details
Main Authors: Halder, A., Rakshit, P., Chakraborty, S., Konar, A., Chakraborty, A., Eunjin Kim, Nagar, A. K.
Format: Conference Proceeding
Language:English
Subjects:
Accuracy
Emotion recognition
Frequency measurement
Frequency modulation
Fuzzy sets
IT2FS
Measurement uncertainty
Reduced IT2FS
Type-2 Fuzzy Sets
Uncertainty
Online Access:Request full text
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Summary:The essence of the paper is to reduce uncertainty in interval type-2 fuzzy sets, and demonstrate the merit of uncertainty reduction in pattern classification problem. The area under the footprint of uncertainty has been used as the measure of uncertainty. A mathematical approach to reduce the area under the footprint of uncertainty has been proposed. Experiments have been designed to compare the relative performance of the classical interval type-2 fuzzy sets with its revised counterpart in emotion recognition from facial expression. Statistical tests performed favor the proposed results of uncertainty reduction. The proposed uncertainty reduction scheme helps in saving approximately 6% gain in classification accuracy with respect to one published work when applied to emotion recognition problem.
ISSN:1098-7584
DOI:10.1109/FUZZ-IEEE.2012.6251363