Monday, November 7, 2011

ISMAR 2011 Paper Highlights

My favorite papers presented at ISMAR 2011.

Robust Planar Target Tracking and Pose Estimation from a Single Concavity
Michael Donoser, Peter Kontschieder, Horst Bischof
Graz University of Technology
"The basic idea is to adapt the classic tracking-by-detection approach, which seeks for the object to be tracked independently in each frame, for tracking non-textured objects. In order to robustly estimate the 3D pose of such objects in each frame, we have to tackle three demanding problems. First, we need to find a stable representation of the object which is discriminable against the background and highly repetitive. Second, we have to robustly relocate this representation in every frame, also during considerable viewpoint changes. Finally, we have to estimate the pose from a single,closed object contour"

Homography-Based Planar Mapping and Tracking for Mobile Phones
Christian Pirchheim, Gerhard Reitmayr
Graz University of Technology
"We present a real-time camera pose tracking and mapping system which uses the assumption of a planar scene to implement a highly efficient mapping algorithm. Our light-weight mapping approach is based on keyframes and plane-induced homographies between them. We solve the planar reconstruction problem of estimating the keyframe poses with an efficient image rectification algorithm.Camera pose tracking uses continuously extended and refined planar point maps and delivers robustly estimated 6DOF poses. We compare system and method with bundle adjustment and monocular SLAM on synthetic and indoor image sequences. We demonstrate large savings in computational effort compared to the monocular SLAM system while the reduction in accuracy remains acceptable."

RGB-D Camera-Based Parallel Tracking and Meshing
Sebastian Lieberknecht, Andrea Huber, Slobodan Ilic, Selim Benhimane
Metaio GmbH
"Compared to standard color cameras, RGB-D cameras are designed to additionally provide the depth of imaged pixels which in turn results in a dense colored 3D point cloud representing the environment from a certain viewpoint. We present a real-time tracking method that performs motion estimation of a consumer RGB-D camera with respect to an unknown environment while at the same time reconstructing this environment as a dense textured mesh."

KinectFusion: Real-Time Dense Surface Mapping and Tracking
Richard A. Newcombe, Shahram Izadi, Otmar Hilliges, David Molyneaux, David Kim, Andrew J. Davison, Pushmeet Kohli, Jamie Shotton, Steve Hodges, Andrew Fitzgibbon
Microsoft Research

Best paper award!
"We present a system for accurate real-time mapping of complex and arbitrary indoor scenes in variable lighting conditions, using only a moving low-cost depth camera and commodity graphics hardware.We fuse all of the depth data streamed from a Kinect sensor into a single global implicit surface model of the observed scene in real-time. The current sensor pose is simultaneously obtained by tracking the live depth frame relative to the global model using a coarse-to-fine iterative closest point (ICP) algorithm, which uses all of the observed depth data available."

My personal favorite!

Light Factorization for Mixed-Frequency Shadows in Augmented Reality
Derek Nowrouzezahrai, Stefan Geiger, Kenny Mitchell, Robert Sumner, Wojciech Jarosz, Markus Gross
Disney Research Zürich
"Integrating animated virtual objects with their surroundings for high-quality augmented reality requires both geometric and radiometric consistency. We focus on the latter of these problems and present an approach that captures and factorizes external lighting in a manner that allows for realistic relighting of both animated and static virtual objects. Our factorization facilitates a combination of hard and soft shadows, with high-performance, in a manner that is consistent with the surrounding scene lighting."

The Argon AR Web Browser and Standards-based AR Application Environment
Blair MacIntyre, Alex Hill, Hafez Rouzati, Maribeth Gandy, Brian Davidson

"In this paper, we present the design and implementation of theArgon AR Web Browser and describe our vision of an AR application environment that leverages the WWW ecosystem. We also describe KARML, our extension to KML (the spatial markup language for Google Earth and Maps), that supports the functionality required for mobile AR. We combine KARML with the full range of standard web technologies to create a standards-based web browser for mobile AR. KARML lets users develop 2D and3D content using existing web technologies and facilitates easy deployment from standard web servers. We highlight a number of projects that have used Argon and point out the ways in which our web-based architecture e has made previously impractical AR concepts possible."

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