Bayesian based 3D shape reconstruction from video
In a video sequence with a 3D rigid object moving, changing shapes of the 2D projections provide interrelated spatio-temporal cues for incremental 3D shape reconstruction. This paper describes a probabilistic approach for intelligent view-integration to build 3D model of vehicles from traffic videos collected from an uncalibrated static camera. The proposed Bayesian net framework allows the handling of uncertainties in a systematic manner. The performance is verified with several types of vehicles in different videos.