Rough Decision Making of Facial Expression Detection
Abstract
This paper introduces a novel framework named Rough Decision Making which extends
the principles of Rough Set Theory. The mathematical model proposed consists of
a fuzzy interval-valued knowledge-based information system that includes a non-empty
finite universe of objects, a derived interval-valued fuzzy set of attributes, and a fuzzy
interval-valued set of decisions. To manage complexity, the roughness of decision-making
is introduced by defining Lower and Upper Rough Decisions for each object. Further
this model is implemented on a real-time affective image database RAF-DB for facial
expression detection. This approach is found to provide a comprehensive analysis of facial
expressions, demonstrating effective classification even in the presence of uncertainty.
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