Machine Learning
Local Grayvalue Invariants for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape quantization and recognition with randomized trees
Neural Computation
Joint Induction of Shape Features and Tree Classifiers
IEEE Transactions on Pattern Analysis and Machine Intelligence
Solution of the simultaneous pose and correspondence problem using Gaussian error model
Computer Vision and Image Understanding
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Model-Based Object Pose in 25 Lines of Code
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Multi-view Matching for Unordered Image Sets, or "How Do I Organize My Holiday Snaps?"
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
An Affine Invariant Interest Point Detector
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Recognition of 3D Textured Objects by Mixing View-Based and Model-Based Representations
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
"living-room": interactive, space-oriented augmented reality
Proceedings of the 12th annual ACM international conference on Multimedia
Real-Time Markerless Tracking for Augmented Reality: The Virtual Visual Servoing Framework
IEEE Transactions on Visualization and Computer Graphics
Keypoint Recognition Using Randomized Trees
IEEE Transactions on Pattern Analysis and Machine Intelligence
Model-Based Motion Capture for Crash Test Video Analysis
Proceedings of the 30th DAGM symposium on Pattern Recognition
Inside looking out camera pose estimation for virtual studio
Graphical Models
Object-adaptive tracking for AR guidance system
VRCAI '08 Proceedings of The 7th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and Its Applications in Industry
Face detection and tracking using a Boosted Adaptive Particle Filter
Journal of Visual Communication and Image Representation
Computer Vision and Image Understanding
Evaluation of the SIFT Object Recognition Method in Mobile Robots
Proceedings of the 2009 conference on Artificial Intelligence Research and Development: Proceedings of the 12th International Conference of the Catalan Association for Artificial Intelligence
Generic Object Recognition in Urban Image Databases
Proceedings of the 2009 conference on Artificial Intelligence Research and Development: Proceedings of the 12th International Conference of the Catalan Association for Artificial Intelligence
Evaluation of the SIFT Object Recognition Method in Mobile Robots
Proceedings of the 2009 conference on Artificial Intelligence Research and Development: Proceedings of the 12th International Conference of the Catalan Association for Artificial Intelligence
Generic Object Recognition in Urban Image Databases
Proceedings of the 2009 conference on Artificial Intelligence Research and Development: Proceedings of the 12th International Conference of the Catalan Association for Artificial Intelligence
Visual content layer for scalable object recognition in urban image databases
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Object recognition using point uncertainty regions as pose uncertainty regions
Image and Vision Computing
Combining Harris interest points and the SIFT descriptor for fast scale-invariant object recognition
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Clustered stochastic optimization for object recognition and pose estimation
Proceedings of the 29th DAGM conference on Pattern recognition
Initial pose estimation for 3D model tracking using learned objective functions
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part II
On-line document registering and retrieving system for AR annotation overlay
Proceedings of the 1st Augmented Human International Conference
Feature tracking for wide-baseline image retrieval
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
Tracking of multiple objects using optical flow based multiscale elastic matching
WDV'05/WDV'06/ICCV'05/ECCV'06 Proceedings of the 2005/2006 international conference on Dynamical vision
Tracking planes with large interframe displacement by fusing template and point based approaches
Proceedings of the 10th International Conference on Virtual Reality Continuum and Its Applications in Industry
Fusion of 3d and appearance models for fast object detection and pose estimation
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part II
Robust pose estimation with 3d textured models
PSIVT'06 Proceedings of the First Pacific Rim conference on Advances in Image and Video Technology
Fusing template and point information to track planes with large interframe displacement
MMM'12 Proceedings of the 18th international conference on Advances in Multimedia Modeling
A convolutional treelets binary feature approach to fast keypoint recognition
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
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We propose a novel approach to point matching under large viewpoint and illumination changes that is suitable for accurate object pose estimation at a much lower computational cost than state-of-the-art methods. Most of these methods rely either on using ad hoc local descriptors or on estimating local affine deformations. By contrast, we treat wide baseline matching of keypoints as a classification problem, in which each class corresponds to the set of all possible views of such a point. Given one or more images of a target object, we train the system by synthesizing a large number of views of individual keypoints and by using statistical classification tools to produce a compact description of this view set. At run-time, we rely on this description to decide to which class, if any, an observed feature belongs. This formulation allows us to use a classification method to reduce matching error rates, and to move some of the computational burden from matching to training, which can be performed beforehand. In the context of pose estimation, we present experimental results for both planar and non-planar objects in the presence of occlusions, illumination changes, and cluttered backgrounds. We will show that our method is both reliable and suitable for initializing real-time applications.