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M.: Pose estimation with radial distortion and unknown focal length
- In: Computer Vision and Pattern Recognition
, 2009
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Cited by 19 (0 self)
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A Column-Pivoting Based Strategy for Monomial Ordering in Numerical Gröbner Basis Calculations
"... Abstract. This paper presents a new fast approach to improving stability in polynomial equation solving. Gröbner basis techniques for equation solving have been applied successfully to several geometric computer vision problems. However, in many cases these methods are plagued by numerical problems. ..."
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Abstract. This paper presents a new fast approach to improving stability in polynomial equation solving. Gröbner basis techniques for equation solving have been applied successfully to several geometric computer vision problems. However, in many cases these methods are plagued by numerical problems. An interesting approach to stabilising the computations is to study basis selection for the quotient space C[x]/I. In this paper, the exact matrix computations involved in the solution procedure are clarified and using this knowledge we propose a new fast basis selection scheme based on QR-factorization with column pivoting. We also propose an adaptive scheme for truncation of the Gröbner basis to further improve stability. The new basis selection strategy is studied on some of the latest reported uses of Gröbner basis methods in computer vision and we demonstrate a fourfold increase in speed and nearly as good over-all precision as the previous SVD-based method. Moreover, we get typically get similar or better reduction of the largest errors. 1 1
A minimal solution for camera calibration using independent pairwise correspondences
- In ECCV
, 2012
"... Abstract. We propose a minimal algorithm for fully calibrating a cam-era from 11 independent pairwise point correspondences with two other calibrated cameras. Unlike previous approaches, our method neither re-quires triple correspondences, nor prior knowledge about the viewed scene. This algorithm c ..."
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Abstract. We propose a minimal algorithm for fully calibrating a cam-era from 11 independent pairwise point correspondences with two other calibrated cameras. Unlike previous approaches, our method neither re-quires triple correspondences, nor prior knowledge about the viewed scene. This algorithm can be used to insert or re-calibrate a new cam-era into an existing network, without having to interrupt operation. Its main strength comes from the fact that it is often difficult to find triple correspondences in a camera network. This makes our algorithm, for the specified use cases, probably the most suited calibration solution that does not require a calibration target, and hence can be performed with-out human interaction.
Localization and Mapping of Surveillance Cameras in City Map
"... Many large cities have installed surveillance cameras to mon-itor human activities for security purposes. An important surveillance application is to track the motion of an object of interest, e.g., a car or a human, using one or more cameras, and plot the motion path in a city map. To achieve this ..."
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Many large cities have installed surveillance cameras to mon-itor human activities for security purposes. An important surveillance application is to track the motion of an object of interest, e.g., a car or a human, using one or more cameras, and plot the motion path in a city map. To achieve this goal, it is necessary to localize the cameras in the city map and to determine the correspondence mappings between the positions in the city map and the camera views. Since the view of the city map is roughly orthogonal to the camera views, there are very few common features between the two views for a computer vision algorithm to correctly identify corresponding points automatically. This paper proposes a method for camera localization and position mapping that requires minimum user inputs. Given approximate corre-sponding points between the city map and a camera view identified by a user, the method computes the orientation and position of the camera in the city map, and determines the mapping between the positions in the city map and the camera view. The performance of the method is assessed in both quantitative tests and practical application. Quantita-tive test results show that the method is accurate and robust in camera localization and position mapping. Application test results are very encouraging, showing the usefulness of the method in real applications.
