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Titlebook: Human Behavior Understanding; 5th International Wo Hyun Soo Park,Albert Ali Salah,Rita Cucchiara Conference proceedings 2014 Springer Inter

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How Do You Like Your Virtual Agent?: Human-Agent Interaction Experience through Nonverbal Features a Moreover, the nonverbal behavior of a person has been known to indicate several social constructs in different settings. In this study, we analyze human-agent interaction from the perspective of the personality of the human and the nonverbal behaviors he/she displays during the interaction. Based o
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A New Multi-modal Dataset for Human Affect Analysisment at various locations during a sequence of debates in a video conference, Skype style arrangement. An additional depth modality was introduced, which permitted the capture of 3D information in addition to the video and audio signals. The dataset consists of 16 participants and is subdivided into
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The Role of Color and Contrast in Facial Age Estimation can be used in creating systems that are not necessarily more accurate in age estimation, but strongly resemble human age estimations. In this paper we investigate the perceptual hypothesis that contrast is a useful cue for estimating age from facial appearance. Using an extensive evaluation paradi
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Dominant Motion Analysis in Regular and Irregular Crowd Scenesfeatures on the scene, and advect them through optical flow. Approximating the moving corner features to individuals, their interaction forces, represented as endothermic reactions in a thermodynamic system, are computed using the enthalpy measure, thus obtaining the potential corner features of int
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Coupling Fall Detection and Tracking in Omnidirectional Camerasfor conventional cameras require extension and modification to work with such cameras. In this paper we use multiple omnidirectional cameras to observe the inhabitants of a room, and use Hierarchical Hidden Markov Models for detecting falls. To track the people in the room, we extend a generative ap
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Learning Sparse Prototypes for Crowd Perception via Ensemble Coding Mechanismsd hierarchical models of visual processing. Here, we extend a biological model of motion processing with a new dictionary learning method tailored for crowd perception. Our approach uses a sparse coding model to learn crowd prototypes. Ensemble coding mechanisms are implemented via structural and lo
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Dyadic Interaction Detection from Pose and Flowinteractions such as a hand shake or a high five, and locating them in time and space. At the core of our method is a pictorial structures model that additionally takes into account the fine-grained movements around the joints of interest during the interaction. Compared to a bag-of-words approach,
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