Active matching for visual tracking
Robotics and Autonomous Systems
Maximum Likelihood Estimation Sample Consensus with Validation of Individual Correspondences
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part I
LSH-RANSAC: an incremental scheme for scalable localization
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Estimation of the epipole using optical flow at antipodal points
Computer Vision and Image Understanding
Motion estimation by decoupling rotation and translation in catadioptric vision
Computer Vision and Image Understanding
1-point RANSAC for EKF-based structure from motion
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Accelerated hypothesis generation for multi-structure robust fitting
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
An M-estimator for high breakdown robust estimation in computer vision
Computer Vision and Image Understanding
Using grid based feature localization for fast image matching
ICIAR'11 Proceedings of the 8th international conference on Image analysis and recognition - Volume Part I
Sub-sampling: Real-time vision for micro air vehicles
Robotics and Autonomous Systems
Self-calibration of wireless cameras with restricted degrees of freedom
Computer Vision and Image Understanding
Robust fitting for multiple view geometry
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part I
Improving image-based localization by active correspondence search
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part I
Towards fast image-based localization on a city-scale
Proceedings of the 15th international conference on Theoretical Foundations of Computer Vision: outdoor and large-scale real-world scene analysis
Enhanced RANSAC sampling based on non-repeating combinations
Proceedings of the 27th Conference on Image and Vision Computing New Zealand
Globally optimal consensus set maximization through rotation search
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part II
Efficient and robust model fitting with unknown noise scale
Image and Vision Computing
| Hi-index | 0.14 |
A randomized model verification strategy for RANSAC is presented. The proposed method finds, like RANSAC, a solution that is optimal with user-specified probability. The solution is found in time that is (i) close to the shortest possible and (ii) superior to any deterministic verification strategy. A provably fastest model verification strategy is designed for the (theoretical) situation when the contamination of data by outliers is known. In this case, the algorithm is the fastest possible (on average) of all randomized \\RANSAC algorithms guaranteeing a confidence in the solution. The derivation of the optimality property is based on Wald's theory of sequential decision making, in particular a modified sequential probability ratio test (SPRT). Next, the R-RANSAC with SPRT algorithm is introduced. The algorithm removes the requirement for a priori knowledge of the fraction of outliers and estimates the quantity online. We show experimentally that on standard test data the method has performance close to the theoretically optimal and is 2 to 10 times faster than standard RANSAC and is up to 4 times faster than previously published methods.