Monocular Model-Based 3D Tracking of Rigid Objects: A Survey
Моноскопическое модельно-ориентированное 3D-отслеживание жёстких объектов: обзор
2005-01-01
SCID: 54.1/v8m62x29
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camera representationmodel-based trackingmonocular 3D trackingrigid object trackingrobust estimation
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Abstract (AI)
Many applications require tracking of complex 3D objects. These include visual servoing of robotic arms on specific target objects, Aug-mented Reality systems that require real-time registration of the object to be augmented, and head tracking systems that sophisticated inter-faces can use. Computer Vision offers solutions that are cheap, practical and non-invasive. This survey reviews the different techniques and approaches that have been developed by industry and research. First, important math-ematical tools are introduced: Camera representation, robust estima-tion and uncertainty estimation. Then a comprehensive study is given of the numerous approaches developed by the Augmented Reality and Robotics communities, beginning with those that are based on point or planar fiducial marks and moving on to those that avoid the need to engineer the environment by relying on natural features such as edges, texture or interest. Recent advances that avoid manual initialization and failures due to fast motion are also presented. The survery con-cludes with the different possible choices that should be made when implementing a 3D tracking system and a discussion of the future of vision-based 3D tracking. Because it encompasses many computer vision techniques from low-level vision to 3D geometry and includes a comprehensive study of the massive literature on the subject, this survey should be the handbook of the student, the researcher, or the engineer who wants to implement a 3D tracking system. 1
Key Findings
1
Comprehensive review of approaches: from point/planar fiducial mark methods to natural-feature methods using edges, texture, or interest points.
2
Positions the survey as a comprehensive reference covering low-level vision to 3D geometry and extensive literature for students, researchers, and engineers.
3
Presents recent advances that remove the need for manual initialization and reduce failures due to fast motion.
4
Provides implementation guidance by enumerating design choices for building vision-based 3D tracking systems.
5
Survey introduces essential mathematical tools for monocular model-based 3D tracking, including camera representation, robust estimation, and uncertainty estimation.
Research Object
Monocular model-based 3D tracking of rigid objects
Research Subject
Techniques, approaches and performance aspects for tracking rigid 3D objects from a single camera, including camera representation, robust estimation, uncertainty estimation, feature types (fiducial, edges, texture, interest points), initialization, and handling fast motion and failure modes
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2005-01-01
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