On The Understanding Of Motion Of Rigid Objects

Odone, Bernardo; Caprile, Bruno; Girosi, Federico; Torre, Vincent

doi:10.1117/12.937730

Cited by 4 publications

(3 citation statements)

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“…It has been tested and is extensively used in several national laboratories and provides calibration data with an accuracy adequate for metrology and stereoscopic vision. The idea of using vanishing points to locate objects in space or to recover the extrinsic parameters of a pair of images has already been suggested [14][15][16]. A modified procedure for measuring the extrinsic parameters, which takes advantage of the a priori information on the class of images to be processed in the edge-detection step, runs on a SUN 3 in Table 3.…”

Section: Discussionmentioning

confidence: 99%

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Using vanishing points for camera calibration

Caprile

Torre

1990

Int J Comput Vision

Self Cite

618

347

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In this article a new method for the calibration of a vision system which consists of two (or more) cameras is presented. The proposed method, which uses simple properties of vanishing points, is divided into two steps. In the first step, the intrinsic parameters of each camera, that is, the focal length and the location of the intersection between the optical axis and the image plane, are recovered from a single image of a cube. In the second step, the extrinsic parameters of a pair of cameras, that is, the rotation matrix and the translation vector which describe the rigid motion between the coordinate systems fixed in the two cameras, are estimated from an image stereo pair of a suitable planar pattern. Firstly, by matching the corresponding vanishing points in the two images the rotation matrix can be computed, then the translation vector is estimated by means of a simple triangulation. The robustness of the method against noise is discussed, and the conditions for optimal estimation of the rotation matrix are derived. Extensive experimentation shows that the precision that can be achieved with the proposed method is sufficient to efficiently perform machine vision tasks that require camera calibration, like depth from stereo and motion from image sequence.

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Section: Discussionmentioning

confidence: 99%

“…Moreover, it can be used by a robot to navigate in an environment where vanishing points can be detected. A preliminary report of this work has already been presented [14].…”

Section: Introductionmentioning

confidence: 99%

Using vanishing points for camera calibration

Caprile

Torre

1990

Int J Comput Vision

Self Cite

618

347

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show abstract

“…A number of camera calibration methods [2][3][4][5][6][7][8][9]12] have recently been reported which either seek calibration cues (e.g., vanishing points [1] due to parallel lines) directly from the scene or only require very simple calibration objects (e.g., simple planar shapes, cubes, etc.). Such methods do not have the problems of current self-calibration methods, and may easily be implemented in practice.…”

Section: Introductionmentioning

confidence: 99%

Recovery of Intrinsic and Extrinsic Camera Parameters using Perspective Views of Rectangles.

Tan

Sullivan²,

Baker³

1995

Procedings of the British Machine Vision Conference 1995

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This paper concerns the recovery of intrinsic and extrinsic camera parameters using perspective views of rectangles. Several algorithms are described. The intrinsic parameters (aspect ratio, effective focal length, and the principal point) are determined in closed-form using a minimum of four views. The recovery of the intrinsic parameters and the rotation angles is independent of the size of the rectangles. The absolute translation is recovered by knowing either the length of one side of the rectangle or the area of the rectangle or any other absolute information. The new method for recovering extrinsic parameters is shown to be significantly more robust than the widely used method based on vanishing points. Experiments with both synthetic and real images are presented.

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Computing camera parameters using vanishing-line information from a rectangular parallelepiped

Wang

Tsai

1990

Machine Vis. Apps.

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On The Understanding Of Motion Of Rigid Objects

Cited by 4 publications

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Using vanishing points for camera calibration

Using vanishing points for camera calibration

Recovery of Intrinsic and Extrinsic Camera Parameters using Perspective Views of Rectangles.

Computing camera parameters using vanishing-line information from a rectangular parallelepiped

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