Optical Flow Estimation: An Error Analysis of Gradient-Based Methods with Local Optimization
IEEE Transactions on Pattern Analysis and Machine Intelligence
Integration, Coordination and Control of Multi-Sensor Robot Systems
Integration, Coordination and Control of Multi-Sensor Robot Systems
The Accuracy of 3D Parameters in Correspondence-based Techniques
The Accuracy of 3D Parameters in Correspondence-based Techniques
Modelling the environment of an exploring vehicle by means of stereo vision
Modelling the environment of an exploring vehicle by means of stereo vision
Obstacle avoidance and navigation in the real world by a seeing robot rover
Obstacle avoidance and navigation in the real world by a seeing robot rover
A Framework for Uncertainty and Validation of 3-D RegistrationMethods Based on Points and Frames
International Journal of Computer Vision
Bootstrap resampling for image registration uncertainty estimation without ground truth
IEEE Transactions on Image Processing
Image registration accuracy estimation without ground truth using bootstrap
CVAMIA'06 Proceedings of the Second ECCV international conference on Computer Vision Approaches to Medical Image Analysis
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A general method of calculating the precision of environmental parameters which differs from conventional methods by finding analytical results, and which does so using only information in the image is discussed. This method called uncertainty-analysis, is applied to the case of first-order-error-based motion algorithms for determining environmental depth by matching corresponding points between two or more frames of a dynamic image sequence. How to calculate the uncertainty of in predicted values for the depth is shown, as well as how to calculate the search region for further instances of the point in subsequent frames, based only on information present in the image. The analysis is applied to a real image sequence with good results.