Structure from image sequences captured through a monocular extra-wide angle lens

Kato, Ryu; Nakanishi,; Shio,; Ishii,

doi:10.1109/cvpr.1994.323925

Cited by 7 publications

(3 citation statements)

References 7 publications

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“…Kato et al used a shape-from-silhouette approach with a fisheye camera to reconstruct a moving object, whose motion was supposed to be determinable [270].…”

Section: Three-dimensional Scene Modelingmentioning

confidence: 99%

Camera Models and Fundamental Concepts Used in Geometric Computer Vision

Sturm

2010

FNT in Computer Graphics and Vision

157

122

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A printed and bound version is available at a special discount price of US35 from Now Publishers. This can be obtained by entering the promotional code CGV006023 on https://www.nowpublishers.com/bookorder.aspx?doi=0600000023&product=CGVInternational audienceThis survey is mainly motivated by the increased availability and use of panoramic image acquisition devices, in computer vision and various of its applications. Different technologies and different computational models thereof exist and algorithms and theoretical studies for geometric computer vision ("structure-from-motion") are often re-developed without highlighting common underlying principles. One of the goals of this survey is to give an overview of image acquisition methods used in computer vision and especially, of the vast number of camera models that have been proposed and investigated over the years, where we try to point out similarities between different models. Results on epipolar and multi-view geometry for different camera models are reviewed as well as various calibration and self-calibration approaches, with an emphasis on non-perspective cameras. We finally describe what we consider are fundamental building blocks for geometric computer vision or structure-from-motion: epipolar geometry, pose and motion estimation, 3D scene modeling, and bundle adjustment. The main goal here is to highlight the main principles of these, which are independent of specific camera models

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“…Kato et al used a shape-from-silhouette approach with a fisheye camera to reconstruct a moving object, whose motion was supposed to be determinable [270].…”

Section: Three-dimensional Scene Modelingmentioning

confidence: 99%

Camera Models and Fundamental Concepts Used in Geometric Computer Vision

Sturm

2010

FNT in Computer Graphics and Vision

157

122

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“…The "shape-from-contour" method has been found to be a relatively simple and yet effective [1][2][3] method that reconstructs the 3D shape of the surface of an object by extracting the contours of the object from sequential images. This method has recently been further improved [4][5][6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Shape from contour using adaptive image selection

Akutsu¹,

Arakawa²,

Murase³

2002

Systems & Computers in Japan

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SUMMARYThe "shape-from-contour method" reconstructs the 3D shape of the surface of an object by extracting its contour from each of a series of successive images of the object. This can be realized by using a CCD camera, and is a relatively accurate method of obtaining environmental information. However, to obtain an accurate result, many images must be processed. Therefore, it is important to select the images depending on their effect on the final result, particularly for high-speed processing.This paper proposes an adaptive image selection (AISE) method which depends on the required accuracy. The method has been applied to objects having various cross-sectional shapes. The errors in shape reconstruction and the number of images required in the conventional method and the proposed method are compared. The experimental results show that the proposed method requires fewer images than the conventional method, particularly when the surface curvature of the object has large variation. The theoretical relationship between the accuracy of the reconstructed shape and the number of images required is also derived.

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“…ITS Intelligent Transportation Systems [1][2][3][4][5] [ [6][7][8][9][10] [ [11][12][13] C. Lai [7] O. Achler [8] Y. Iwasaki [9] m K. Kato [10] 4. 5.…”

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confidence: 99%

A Position Estimation Based on Tire-Road Contact Points Considering Displacements of Two Concentric Circles on a Circular Fisheye Image

Hirose

Takenaka

Hama

2010

Transactions of ISCIE

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In this paper, we propose a new method for estimating the positions on a road based on detected tire-road contact points taking the distortion on circular fisheye images into consideration. In our proposed method, we use the distortion parameters of two concentric circles composed of the inner wheel and the outer tire by considering projection system of fisheye lens, and the searching the gray scale profiles in the vertical direction are derived from each pixel that is the outline of the wheel region. The effectiveness of the proposed method is confirmed through experimental results.

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Structure from image sequences captured through a monocular extra-wide angle lens

Cited by 7 publications

References 7 publications

Camera Models and Fundamental Concepts Used in Geometric Computer Vision

Camera Models and Fundamental Concepts Used in Geometric Computer Vision

Shape from contour using adaptive image selection

A Position Estimation Based on Tire-Road Contact Points Considering Displacements of Two Concentric Circles on a Circular Fisheye Image

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