Hand2Face: Automatic Synthesis and Recognition of Hand Over Face Occlusions

A person's face discloses important information about their affective state. Although there has been extensive research on recognition of facial expressions, the performance of existing approaches is challenged by facial occlusions. Facial occlusions are often treated as noise and discarded in recognition of affective states. However, hand over face occlusions can provide additional information for recognition of some affective states such as curiosity, frustration and boredom. One of the reasons that this problem has not gained attention is the lack of naturalistic occluded faces that contain hand over face occlusions as well as other types of occlusions. Traditional approaches for obtaining affective data are time demanding and expensive, which limits researchers in affective computing to work on small datasets. This limitation affects the generalizability of models and deprives researchers from taking advantage of recent advances in deep learning that have shown great success in many fields but require large volumes of data. In this paper, we first introduce a novel framework for synthesizing naturalistic facial occlusions from an initial dataset of non-occluded faces and separate images of hands, reducing the costly process of data collection and annotation. We then propose a model for facial occlusion type recognition to differentiate between hand over face occlusions and other types of occlusions such as scarves, hair, glasses and objects. Finally, we present a model to localize hand over face occlusions and identify the occluded regions of the face.Comment: Accepted to International Conference on Affective Computing and Intelligent Interaction (ACII), 201

Journey Beyond the Fair

Journey Beyond the Fair will combine a vast virtual world environment and hand-held devices to develop a tightly coupled home-school-museum paradigm that enhances traditional exhibits. This paradigm is designed to work as a national model where informal humanities education institutions can add depth of learning and heighten the level of interactivity and personalization of an onsite experience by strengthening the connections to a home/school-based virtual world experience. While in this instance we are addressing the 1964/65 New York World's Fair, institutions can adapt the concept based on subjects pertinent to their facility, culture and demographic visitation needs

Development of primary invasive pneumococcal disease caused by serotype 1 pneumococci is driven by early increased type I interferon response in the lung

The pneumococcus is the world's foremost respiratory pathogen, but the mechanisms allowing this pathogen to proceed from initial asymptomatic colonization to invasive disease are poorly understood. We have examined the early stages of invasive pneumococcal disease (IPD) by comparing host transcriptional responses to an invasive strain and a noninvasive strain of serotype 1 Streptococcus pneumoniae in the mouse lung. While the two strains were present in equal numbers in the lung 6 h after intranasal challenge, only the invasive strain (strain 1861) had invaded the pleural cavity at that time point; this correlated with subsequent development of bacteremia in mice challenged with strain 1861 but not the noninvasive strain (strain 1). Progression beyond the lung was associated with stronger induction of the type I interferon (IFN-I) response in the lung at 6 h. Suppression of the IFN-I response through administration of neutralizing antibody to IFNAR1 (the receptor for type I interferons) led to significantly reduced invasion of the pleural cavity by strain 1861 at 6 h postchallenge. Our data suggest that strong induction of the IFN-I response is a key factor in early progression of invasive serotype 1 strain 1861 beyond the lung during development of IPD