Dynamic Scene Reconstruction for 3D Virtual Guidance

In this paper a system is presented able to reproduce the actions of multiple moving objects into a 3D model. A multi-camera system is used for automatically detect, track and classify the objects. Data fusion from multiple sensors allows to get a more precise estimation of the position of detected moving objects and to solve occlusions problem. These data are then used to automatically place and animate objects avatars in a 3D virtual model of the scene, thus allowing users connected to this system to receive a 3D guide into the monitored environment.

[1]  Marco Fiocco,et al.  Multisensor fusion for volumetric reconstruction of large outdoor areas , 2005, Fifth International Conference on 3-D Digital Imaging and Modeling (3DIM'05).

[2]  Fernando Jaureguizar,et al.  Photorealistic 3D reconstruction from handheld cameras , 2005, Machine Vision and Applications.

[3]  Luca Iocchi,et al.  A Stereo Vision System for 3D Reconstruction and Semi-Automatic Surveillance of Museum Areas , 2003 .

[4]  Takeo Kanade,et al.  Algorithms for cooperative multisensor surveillance , 2001, Proc. IEEE.

[5]  Roger Y. Tsai,et al.  A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses , 1987, IEEE J. Robotics Autom..

[6]  Carlo S. Regazzoni,et al.  A multi-feature object association framework for overlapped field of view multi-camera video surveillance systems , 2005, IEEE Conference on Advanced Video and Signal Based Surveillance, 2005..

[7]  Gabriel Taubin,et al.  Real-Time Median Filtering for Embedded Smart Cameras , 2006, Fourth IEEE International Conference on Computer Vision Systems (ICVS'06).

[8]  Dorin Comaniciu,et al.  Real-time tracking of non-rigid objects using mean shift , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[9]  Thomas H. Reiss,et al.  The revised Fundamental Theorem of Moment Invariants , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  Takeo Kanade,et al.  Introduction to the Special Section on Video Surveillance , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Greg Welch,et al.  Welch & Bishop , An Introduction to the Kalman Filter 2 1 The Discrete Kalman Filter In 1960 , 1994 .

[12]  Suya You,et al.  3D video surveillance with Augmented Virtual Environments , 2003, IWVS '03.