Object pose from 2-D to 3-D point and line correspondences
International Journal of Computer Vision
Contour Tracking in Clutter: A Subset Approach
International Journal of Computer Vision
Trust-region methods
Probabilistic Data Association Methods for Tracking Complex Visual Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Contour Tracking by Stochastic Propagation of Conditional Density
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Elliptical Head Tracking Using Intensity Gradients and Color Histograms
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Real-time object tracking using bounded irregular pyramids
Pattern Recognition Letters
Posterior probability measure for image matching
Pattern Recognition
EURASIP Journal on Advances in Signal Processing
Mathematical model of blob matching and modified Bhattacharyya coefficient
Image and Vision Computing
ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
Accurate appearance-based Bayesian tracking for maneuvering targets
Computer Vision and Image Understanding
Robust human tracking based on multi-cue integration and mean-shift
Pattern Recognition Letters
Adaptive pyramid mean shift for global real-time visual tracking
Image and Vision Computing
Generalizing Inverse Compositional and ESM Image Alignment
International Journal of Computer Vision
Sense-Through-Foliage target detection using UWB radar sensor networks
Pattern Recognition Letters
Tracking people in video sequences using multiple models
Multimedia Tools and Applications
Multibandwidth kernel-based object tracking
Advances in Artificial Intelligence - Special issue on machine learning paradigms for modeling spatial and temporal information in multimedia data mining
Geolocation of Multiple Targets from Airborne Video Without Terrain Data
Journal of Intelligent and Robotic Systems
QP_TR trust region blob tracking through scale-space with automatic selection of features
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part I
Robust object tracking algorithm in natural environments
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part II
PR'05 Proceedings of the 27th DAGM conference on Pattern Recognition
A comparative evaluation of template and histogram based 2d tracking algorithms
PR'05 Proceedings of the 27th DAGM conference on Pattern Recognition
Adaptive object tracking with online statistical model update
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part II
Blob tracking with adaptive feature selection and accurate scale determination
ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part I
Real-time vision tracking algorithm
ICCSA'06 Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part V
Inverse composition for multi-kernel tracking
ICVGIP'06 Proceedings of the 5th Indian conference on Computer Vision, Graphics and Image Processing
Real-Time tracking using multiple target models
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part I
A new perspective on object tracking based on BYY and five action circling
IScIDE'11 Proceedings of the Second Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
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Abstract--Optimization methods based on iterative schemes can be divided into two classes: line-search methods and trust-region methods. While line-search techniques are commonly found in various vision applications, not much attention is paid to trust-region ones. Motivated by the fact that line-search methods can be considered as special cases of trust-region methods, we propose to establish a trust-region framework for real-time tracking. Our approach is characterized by three key contributions. First, since a trust-region tracking system is more effective, it often yields better performances than the outcomes of other trackers that rely on iterative optimization to perform tracking, e.g., a line-search-based mean-shift tracker. Second, we have formulated a representation model that uses two coupled weighting schemes derived from the covariance ellipse to integrate an object's color probability distribution and edge density information. As a result, the system can address rotation and nonuniform scaling in a continuous space, rather than working on some presumably possible discrete values of rotation angle and scale. Third, the framework is very flexible in that a variety of distance functions can be adapted easily. Experimental results and comparative studies are provided to demonstrate the efficiency of the proposed method.