3D Reconstruction and Motion Analysis
of Static and Dynamic Scenes
Jana Kosecka, George Mason University
Yi Ma, University of Illinois at Urbana-Champaign
Shankar Sastry, University of California at Berkeley
Stefano Soatto, University of California at Los Angeles
R. Vidal, Johns Hopkins University
Abstract
This tutorial will present the state of the art in 3D reconstruction
and camera pose recovery from multiple views of static and dynamical
scenes. Applications of the techniques presented include autonomous
navigation, building 3D models from video, tracking, visual surveillance,
augmented reality and special effects for entertainment. The course
is based on a recently published textbook co-authored by the organizers,
and includes exercises, live demonstrations and sample code of the
covered techniques.
Upon completing the course, participants should possess the tools
necessary to reconstruct the 3D shape of objects or scenes from
video of set of photographs, calibrate cameras and recover geometric
properties of dynamic scenes including multiple moving objects.
Target Audience
Robotics researchers interested in using vision as a sensor for
control tasks (navigation, manipulation, tracking, docking etc.)
and 3-D model acquisition tasks. Robotics researchers interested
in sensor networks and smart environments, medical, mobile and humanoid
robotics, virtual and mixed reality.
Website
http://cs.gmu.edu/~kosecka/ICRA04/ICRA
Tutorial Web Page.htm
Registration
To attend this tutorial, register for tutorial
T-TF-1 by advance registration deadline.
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