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Machine Learning for Social Behavior Understanding

Human brain has an ability to perform a massive processing of auxiliary information such as visual cues, cognitive and social interactions, contextual and spatio-temporal data. Similarly to a human brain, social behavioral cues can aid the reliable decision-making of a biometric security system. Being an integral part of human behavior, social interactions are likely to possess unique behavioral patterns. This state-of-the-art review paper discusses an emerging person recognition approach based on the in-depth analysis of individuals' social behavior in order to enhance the performance of a traditional biometric system. The social behavioral information can be mined from their offline or online interactions, and can be identified as a set of Social Behavioral Biometric (SBB) features. These features could be used on their own or further combined with other behavioral and physiological patters, and classification can be enhanced by the use of machine learning approaches. An overview of open problems and challenges as well as applications of studying social behavior in various domains concludes this paper.