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This paper proposed an approach of human behavior modeling based on Discriminative Random Fields. In this model, by introducing the hidden behavior feature functions and time window parameters, the Classical CRFs models was extended to spatio-temporal fields. And feature templates were designed to capture the dynamics of human motions. Due to the(More)
This paper addresses the problem of group path planning while maintaining group coherence and persistence. Group coherence ensures that a group minimizes both longitudinal and lateral dispersion, and is achieved with the introduction of a deformation penalty to the cost formulation. When the deformation penalty is significantly high, a group may split and(More)
Considering the increasing collections of motion capture data, motion retrieval in large motion databases is gaining in importance. In this paper, we introduce kinetic interval features describing the movement trend of motions. In our approach, motion files are decomposed into kinetic intervals. For each joint in a kinetic interval, we define the kinetic(More)
Audience engagement is an important indicator of the quality of the performing arts but hard to measure. Psychophysiological measurements are promising research methods for perceiving and understanding audience's responses in real-time. Currently, such research are conducted by collecting biometric data from audience when they are watching a performance. In(More)
Crowd movement is a common but complicated phenomenon in our daily lives. The behaviors of crowds can be affected by both individual and crowd. Most previous research could be categorized as either agent-based methods [van den Berg et al. 2009], which have advantage on simulating individual behaviors, or continuous methods [Narain et al. 2009] which are(More)
This course will provide a comprehensive overview of navigation structures and algorithms for achieving real-time dynamic navigation for the next generation of computer games. Building on top of classical techniques in computational geometry and discrete search, we will introduce recent developments in real-time planning and discrete environment(More)
An adaptive time-step approach is proposed to perform real-time particle fluid simulation. In traditional adaptive approaches, the iterative process of each element updating is limited to the minimum and fixed time step, which results in the computational resources wasting. This paper solved such a problem by adjusting the element updating periodicity with(More)