V-GRAFFER, a system for Visual GRoup AFFect Recognition, Part I: Foundations

Abstract

In this paper, we present our research towards building V-GRAFFER, a system for Visual GRoup AFFect Recognition. Specifically, V-GRAFFER aims at the development and provision of services with regard to the recognition of the emotional state of groups of people. At this stage of the V-GRAFFER development, implemented services are oriented towards detecting and drawing conclusions about students who attend educational events such as lectures, question and answer (Q&A) sessions, or lab participation. Specific functionalities of the current version of V-GRAFFER include processes for data collection, lecture experiments under real conditions, algorithms for sample auto-extraction, and optimized approaches. These functionalities allowed the collection of data of various educational events under real conditions and the creation of flexible databases of appropriate samples for drawing conclusions with regard to emotion detection of groups of people. Furthermore, we devised and implemented innovative algorithms to identify and classify group samples from recorded educational events. These algorithms have been evaluated and improved via continuous cycles of development-testing-evaluation in a variety of experiments. Finally, we constructed completed databases of group samples which are correlated with each other based on time, depth of time and educational settings.