Title :
Bayesian based 3D shape reconstruction from video
Author :
Ghosh, Nirmalya ; Bhanu, Bir
Author_Institution :
Center for Res. in Intell. Syst. (CRIS), Univ. of California, Riverside, CA
Abstract :
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.
Keywords :
Bayes methods; image reconstruction; image sequences; probability; 2D projection; 3D rigid moving object; Bayesian 3D shape reconstruction; intelligent view-integration; probabilistic approach; uncalibrated static camera; uncertainty handling; vehicle traffic video; video sequence; Bayesian methods; Cameras; Image reconstruction; Shape; Stochastic processes; Tracking; Traffic control; Uncertainty; Vehicles; Video sequences; 3D shape from video; Learning;
Conference_Titel :
Image Processing, 2008. ICIP 2008. 15th IEEE International Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-1765-0
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2008.4711964
