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Video driven pedestrian visualization with characteristic appearances

Augmented virtual environment (AVE) could visualize plausible live views from videos by projecting dynamic imagery to the 3D environment. Static objects in a video can be rendered in new views since they are easily modeled beforehand, while moving ones that don't have exact online models will be distorted from different views without proper depth. To cope with the problem, we introduce a novel method to visualize pedestrians, which are common in outdoor surveillance. Our method detects pedestrians and produces their trajectories. Then such pedestrian characteristic appearances as geometric information, texture and walking animation are transferred to a stand-in 3D animation model in the virtual environment. Experiments show our visualization can reveal person's characteristic appearances.