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Facial Descriptors for Human Interaction Recognition In Still Images
This paper presents a novel approach in a rarely studied area of computer
vision: Human interaction recognition in still images. We explore whether the
facial regions and their spatial configurations contribute to the recognition
of interactions. In this respect, our method involves extraction of several
visual features from the facial regions, as well as incorporation of scene
characteristics and deep features to the recognition. Extracted multiple
features are utilized within a discriminative learning framework for
recognizing interactions between people. Our designed facial descriptors are
based on the observation that relative positions, size and locations of the
faces are likely to be important for characterizing human interactions. Since
there is no available dataset in this relatively new domain, a comprehensive
new dataset which includes several images of human interactions is collected.
Our experimental results show that faces and scene characteristics contain
important information to recognize interactions between people