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Catheter Tracking via Online Learning for Dynamic Motion Compensation in Transcatheter Aortic Valve Implantation

by Peng Wang, Yefeng Zheng, Matthias John, Dorin Comaniciu
"... Abstract. Dynamic overlay of 3D models onto 2D X-ray images has important applications in image guided interventions. In this paper, we present a novel catheter tracking for motion compensation in the Transcatheter Aortic Valve Implantation(TAVI). To address such challenges as catheter shape and app ..."
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current state-of-the-art tracking methods in tracking catheters for clinical applications. 1

Efficient region tracking with parametric models of geometry and illumination

by Gregory D. Hager, Peter N. Belhumeur - PAMI , 1998
"... Abstract—As an object moves through the field of view of a camera, the images of the object may change dramatically. This is not simply due to the translation of the object across the image plane. Rather, complications arise due to the fact that the object undergoes changes in pose relative to the v ..."
Abstract - Cited by 563 (30 self) - Add to MetaCart
to the viewing camera, changes in illumination relative to light sources, and may even become partially or fully occluded. In this paper, we develop an efficient, general framework for object tracking—one which addresses each of these complications. We first develop a computationally efficient method

CONDENSATION -- conditional density propagation for visual tracking

by Michael Isard, Andrew Blake , 1998
"... The problem of tracking curves in dense visual clutter is challenging. Kalman filtering is inadequate because it is based on Gaussian densities which, being unimodal, cannot represent simultaneous alternative hypotheses. The Condensation algorithm uses “factored sampling”, previously applied to th ..."
Abstract - Cited by 1503 (12 self) - Add to MetaCart
The problem of tracking curves in dense visual clutter is challenging. Kalman filtering is inadequate because it is based on Gaussian densities which, being unimodal, cannot represent simultaneous alternative hypotheses. The Condensation algorithm uses “factored sampling”, previously applied

Contour Tracking By Stochastic Propagation of Conditional Density

by Michael Isard, Andrew Blake , 1996
"... . In Proc. European Conf. Computer Vision, 1996, pp. 343--356, Cambridge, UK The problem of tracking curves in dense visual clutter is a challenging one. Trackers based on Kalman filters are of limited use; because they are based on Gaussian densities which are unimodal, they cannot represent s ..."
Abstract - Cited by 661 (23 self) - Add to MetaCart
. In Proc. European Conf. Computer Vision, 1996, pp. 343--356, Cambridge, UK The problem of tracking curves in dense visual clutter is a challenging one. Trackers based on Kalman filters are of limited use; because they are based on Gaussian densities which are unimodal, they cannot represent

Author manuscript, published in "Dans The 1st International Workshop on Machine Learning for Vision-based Motion Analysis- MLVMA’08 (2008)" Learning Bayesian Tracking for Motion Estimation ⋆

by Michael Felsberg, Fredrik Larsson , 2008
"... Abstract. A common computer vision problem is to track a physical object through an image sequence. In general, the observations that are made in a single image determine the actual state only partially and information from several views has to be merged. A principled and wellestablished way of fusi ..."
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and the system and measurement models are learned from a training set. The results from the channel-based tracker are compared to state-of-the-art tracking methods based on particle filters, using a standard dataset from the literature. A simple computer vision experiment is shown to illustrate possible

A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking

by M. Sanjeev Arulampalam, Simon Maskell, Neil Gordon - IEEE TRANSACTIONS ON SIGNAL PROCESSING , 2002
"... Increasingly, for many application areas, it is becoming important to include elements of nonlinearity and non-Gaussianity in order to model accurately the underlying dynamics of a physical system. Moreover, it is typically crucial to process data on-line as it arrives, both from the point of view o ..."
Abstract - Cited by 2006 (2 self) - Add to MetaCart
of storage costs as well as for rapid adaptation to changing signal characteristics. In this paper, we review both optimal and suboptimal Bayesian algorithms for nonlinear/non-Gaussian tracking problems, with a focus on particle filters. Particle filters are sequential Monte Carlo methods based on point mass

Real-Time Tracking of Non-Rigid Objects using Mean Shift

by Dorin Comaniciu, Visvanathan Ramesh, Peter Meer - IEEE CVPR 2000 , 2000
"... A new method for real-time tracking of non-rigid objects seen from a moving camera isproposed. The central computational module is based on the mean shift iterations and nds the most probable target position in the current frame. The dissimilarity between the target model (its color distribution) an ..."
Abstract - Cited by 815 (19 self) - Add to MetaCart
A new method for real-time tracking of non-rigid objects seen from a moving camera isproposed. The central computational module is based on the mean shift iterations and nds the most probable target position in the current frame. The dissimilarity between the target model (its color distribution

The PASCAL Visual Object Classes (VOC) Challenge

by M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, A. Zisserman - INTERNATIONAL JOURNAL OF COMPUTER VISION
"... ... and detection, providing the vision and machine learning communities with a standard dataset of images and annotation, and standard evaluation procedures. Organised annually from 2005 to present, the challenge and its associated dataset has become accepted as the benchmark for object detection. ..."
Abstract - Cited by 629 (20 self) - Add to MetaCart
. This paper describes the dataset and evaluation procedure. We review the state-of-the-art in evaluated methods for both classification and detection, analyse whether the methods are statistically different, what they are learning from the images (e.g. the object or its context), and what the methods find

Hierarchical phrase-based translation

by David Chiang - Computational Linguistics , 2007
"... We present a statistical machine translation model that uses hierarchical phrases—phrases that contain subphrases. The model is formally a synchronous context-free grammar but is learned from a parallel text without any syntactic annotations. Thus it can be seen as combining fundamental ideas from b ..."
Abstract - Cited by 597 (9 self) - Add to MetaCart
the Alignment Template System, a state-of-the-art phrasebased system. 1.

Marker tracking and HMD calibration for a video-based augmented reality conferencing system

by Hirokazu Kato - in The 2nd International Workshop on Augmented Reality (IWAR 99 , 1999
"... We describe an augmented reality conferencing system which uses the overlay of virtual images on the real world. Remote collaborators are represented on Virtual Monitors which can be freely positioned about a user in space. Users can collaboratively view and interact with virtual objects using a sha ..."
Abstract - Cited by 527 (26 self) - Add to MetaCart
shared virtual whiteboard. This is possible through precise virtual image registration using fast and accurate computer vision techniques and HMD calibration. We propose a method for tracking fiducial markers and a calibration method for optical see-through HMD based on the marker tracking. 1.
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