Book Chapter10.1007/978-1-4471-1921-0_39
Model-based Tracking
Anthony D. Worrall,Roland F. Marslin,Geoffrey D. Sullivan,Keith D. Baker +3 more
- 01 Jan 1991
- pp 310-318
TL;DR: Model-based vision techniques originally developed for the recognition and pose recovery of a vehicle in a single image are used here to track a vehicle through a sequence of images.
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Abstract: Model-based vision techniques originally developed for the recognition and pose recovery of a vehicle in a single image, are used here to track a vehicle through a sequence of images The knowledge of the position of the camera with respect to the ground plane is used to reduce the search space of possible vehicle positions from six dimensions to three
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Citations
Model-based object tracking in monocular image sequences of road traffic scenes
TL;DR: An elaborate combination of various techniques has enabled us to track vehicles under complex illumination conditions and over long monocular image sequences, and open problems as well as future work are outlined.
768
Robust Multiple Car Tracking with Occlusion Reasoning
Dieter Koller,Joseph Weber,Jitendra Malik +2 more
- 01 Jun 1994
TL;DR: This work proposes a new approach for tracking vehicles in road traffic scenes using an explicit occlusion reasoning step and employs a contour tracker based on intensity and motion boundaries to obtain robust motion estimates and trajectories for vehicles even in the case of occlusions.
Model-Based Localisation and Recognition of Road Vehicles
TL;DR: A form of the generalised Hough transform is used in conjuction with explicit probability-based voting models to find consistent matches and to identify the approximate poses of vehicles in traffic scenes, which under normal conditions stand on the ground-plane.
166
Visual interpretation of known objects in constrained scenes
TL;DR: The experiments with machine vision raise questions about the part played by perceptual context for object recognition in natural vision, and the neural mechanisms which might serve such a role.
145
Model-Based Object Tracking in Traffic Scenes
Dieter Koller,Konstantinos Daniilidis,T. Thórhallson,Hans-Hellmut Nagel,Hans-Hellmut Nagel +4 more
- 19 May 1992
TL;DR: This contribution addresses the problem of detection and tracking of moving vehicles in image sequences from traffic scenes recorded by a stationary camera by using a parameterized vehicle model and a recursive estimator based on a motion model for motion estimation.
References
Fitting parameterized three-dimensional models to images
TL;DR: Current methods of parameter solving are extended to handle objects with arbitrary curved surfaces and with any number of internal parameters representing articulation, variable dimensions, or surface deformations to allow model-based vision to be used for a much wider class of problems than was possible with previous methods.
RAPID - a video rate object tracker.
Chris Harris,Carl Stennett +1 more
- 01 Jan 1990
TL;DR: Three-dimensional (3D) Model-Based Vision enables observed image features to be used to determine the pose (ie. position and attitude) of a known 3D object with respect to the camera (or alternatively, the viewpoint of the camera withrespect to the model).
Fitting Parameterized 3-D Models to Images
David G. Lowe
- 01 Dec 1989
TL;DR: Current methods of parameter solving to handle objects with arbitrary curved surfaces and with any number of internal parameters representing articulations, variable dimensions, or surface deformations are extended.
66
Tracking Objects Using Image Disparities.
Alistair J. Bray
- 01 Jan 1989
TL;DR: In this article, a method and results for a system that finds and tracks known polyhedral objects in 3-space, given a sequence of grey-level images, were presented.
Tracking objects using image disparities
TL;DR: A system that finds and tracks known polyhedral objects in 3-space, given a sequence of grey-level images is presented, which integrates three established algorithms in a novel way.
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