Designing a mirror to realize a given projection

Hicks, R. Andrew

doi:10.1364/josaa.22.000323

Cited by 37 publications

(20 citation statements)

References 4 publications

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“…Thus, the challenge is to find shapes that obtain a wide field of view without distorting the image. R. Andrew Hicks [8][9][10][11][12] presents a new technique for finding such approximations and applies it to the design of a rear-view mirror for an automobile that has no blind spot and minimal distortion. With this method, we design a rear-view mirror with a scale factor of 2.…”

Section: Tool Path Generation For Fts Cutting 31 Design Of a Rear-vimentioning

confidence: 99%

Fast tool servo diamond turning of optical freeform surfaces for rear-view mirrors

Tian

Yin

2015

Int J Adv Manuf Technol

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Optical freeform surfaces have been applied in optoelectronic systems more and more widely, but it is difficult to fabricate this kind of freeform surface optics with high quality and high efficiency. Ultra-precision diamond turning machining technology based on a fast tool servo system is an effective and precise process for fabricating optical freeform surfaces. This paper develops a novel fast tool servo system, which has a total stroke of 30 mm and a maximum acceleration of 920 m/s 2 . In this paper, we develop a theoretical and experimental investigation on the 3D surface generation of a rear-view mirror which is a typical optical freeform surface in single-point diamond tuning using a fast tool servo system. The experimental results are tested and analyzed, which indicate that the performances are satisfied. The field of view obtained by the designed rear-view mirror is much larger than the flat mirror, while the distortion is minimal.

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Section: Tool Path Generation For Fts Cutting 31 Design Of a Rear-vimentioning

confidence: 99%

Fast tool servo diamond turning of optical freeform surfaces for rear-view mirrors

Tian

Yin

2015

Int J Adv Manuf Technol

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“…Gaspar et al proposed a general approach allowing to derive several of the above mirror designs in a unified framework [156,157]. Hicks as well as Menegatti formulated and provided a solution to the so-called prescribed projection problem [221,341]: the input is a desired mapping between an object surface and the image plane of a camera in a given position. The goal is to compute a mirror and its location, that together realize this mapping, i.e., the image taken by the resulting catadioptric system is as specified.…”

Section: Non-central Catadioptric Camerasmentioning

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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“…Baker and Nayar [68] derive the complete class of singlelens single-mirror catadioptic cameras that has a single viewpoint. Hicks [69] proposes a technique of designing a mirror to realize any given projection in a numerical approximation manner.…”

Section: A Spatially Variant Filter 1) Depth Estimationmentioning

confidence: 99%

Computational Cameras: Convergence of Optics and Processing

Zhou

Nayar

2011

IEEE Trans. on Image Process.

105

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Abstract-A computational camera uses a combination of optics and processing to produce images that cannot be captured with traditional cameras. In the last decade, computational imaging has emerged as a vibrant field of research. A wide variety of computational cameras has been demonstrated to encode more useful visual information in the captured images, as compared with conventional cameras. In this paper, we survey computational cameras from two perspectives. First, we present a taxonomy of computational camera designs according to the coding approaches, including object side coding, pupil plane coding, sensor side coding, illumination coding, camera arrays and clusters, and unconventional imaging systems. Second, we use the abstract notion of light field representation as a general tool to describe computational camera designs, where each camera can be formulated as a projection of a high-dimensional light field to a 2-D image sensor. We show how individual optical devices transform light fields and use these transforms to illustrate how different computational camera designs (collections of optical devices) capture and encode useful visual information.

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Designing a mirror to realize a given projection

Cited by 37 publications

References 4 publications

Fast tool servo diamond turning of optical freeform surfaces for rear-view mirrors

Fast tool servo diamond turning of optical freeform surfaces for rear-view mirrors

Camera Models and Fundamental Concepts Used in Geometric Computer Vision

Computational Cameras: Convergence of Optics and Processing

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