Artificial Intelligence - Special volume on computer vision
In Defense of the Eight-Point Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
Heteroscedastic Regression in Computer Vision: Problems with Bilinear Constraint
International Journal of Computer Vision - Special issue on a special section on visual surveillance
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
The Role of Total Least Squares in Motion Analysis
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Computational Statistics & Data Analysis
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This paper is concerned with solution of the consistent fundamental matrix estimation in a quadratic measurement error model. First an extended system for determining the estimator is proposed, and an efficient implementation for solving the system-a continuation method is developed to fix on an interval in which a local minimum belongs. Then an optimization method using a quadratic interpolation is used to exactly locate the minimum. The proposed method avoids solving total eigenvalue problems. Thus the computational cost is significantly reduced. Synthetic and real images are used to verify and illustrate the effectiveness of the proposed approach.