Can We Calibrate a Camera Using an Image of a Flat,Textureless Lambertian Surface?

Kang, Sing Bing; Weiss, Richard

doi:10.1007/3-540-45053-x_41

Cited by 58 publications

(56 citation statements)

References 13 publications

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“…The chosen model for Panoptic camera is the Kang-Weiss model [24]. The Kang-Weiss model takes into account the pixel position in the camera image frame, the camera focal length and a camera constant named the vignetting factor.…”

Section: Vignetting Correctionmentioning

confidence: 99%

Image Blending in a High Frame Rate FPGA-based Multi-Camera System

Popović

Seyid

Akın

et al. 2013

J Sign Process Syst

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Panoptic is a custom spherical light field camera used as a polydioptric system where imagers are distributed over a hemispherical surface, each having its own vision of the surroundings and a distinct focal plane. The spherical light field camera records light information from any direction around its center. This paper revises previously developed Nearest Neighbor and Linear blending techniques. Novel Gaussian blending and Restricted Gaussian blending techniques for vision reconstruction of a virtual observer located inside the spherical geometry are presented. These new blending techniques improve the output quality of the reconstructed image with respect to the ordinary stitching techniques and simpler image blending algorithms. A comparison of the developed blending algorithms is also given in this paper. A hardware architecture based on Field Programmable Gate Arrays (FPGA) enabling the real-time implementation of the blending algorithms is presented, along with the imaging results and resource utilization comparison. A recorded omnidirectional video is attached as a supplementary material.

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Section: Vignetting Correctionmentioning

confidence: 99%

Image Blending in a High Frame Rate FPGA-based Multi-Camera System

Popović

Seyid

Akın

et al. 2013

J Sign Process Syst

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show abstract

“…The chosen model for the Panoptic camera is the Kang-Weiss model [17]. The Kang-Weiss model takes into account the pixel position in the camera image frame, the camera focal length and a camera constant named the vignetting factor.…”

Section: B Vignetting Correction and Gaussian Blendingmentioning

confidence: 99%

Real-time implementation of Gaussian image blending in a spherical light field camera

Popović

Afshari

Schmid

et al. 2013

2013 IEEE International Conference on Industrial Technology (ICIT)

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Abstract-Panoptic is a custom spherical light field camera used as a polydioptric system where imagers are distributed over a spherical geometry, each having its own vision of the surrounding and a distinct focal plane. The spherical light field camera records light information from any direction around its center. A novel Gaussian blending technique is presented for vision reconstruction of a virtual observer located inside the spherical geometry of this camera. This blending technique improves the output quality of the reconstructed image with respect to ordinary stitching techniques and simpler image blending algorithms. A hardware architecture based on Field Programmable Gate Arrays (FPGA) with the real-time implementation of the Gaussian blending algorithm using the spherical light field camera is presented, along with the imaging results.

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“…Vignetting can be estimated by imaging a uniformly illuminated flat textureless Lambertian surface, and comparing the intensity of every pixel with that of the center pixel (which is assumed to have no vignetting) [25,26]. Unfortunately, realizing such capture conditions is difficult.…”

Section: Related Workmentioning

confidence: 99%

Priors for Large Photo Collections and What They Reveal about Cameras

Kuthirummal

Agarwala

Goldman

et al. 2008

Lecture Notes in Computer Science

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Abstract.A large photo collection downloaded from the internet spans a wide range of scenes, cameras, and photographers. In this paper we introduce several novel priors for statistics of such large photo collections that are independent of these factors. We then propose that properties of these factors can be recovered by examining the deviation between these statistical priors and the statistics of a slice of the overall photo collection that holds one factor constant. Specifically, we recover the radiometric properties of a particular camera model by collecting numerous images captured by it, and examining the deviation of this collection's statistics from that of a broader photo collection whose camera-specific effects have been removed. We show that using this approach we can recover both a camera model's non-linear response function and the spatially-varying vignetting of the camera's different lens settings. All this is achieved using publicly available photographs, without requiring images captured under controlled conditions or physical access to the cameras. We also apply this concept to identify bad pixels on the detectors of specific camera instances. We conclude with a discussion of future applications of this general approach to other common computer vision problems.

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Can We Calibrate a Camera Using an Image of a Flat,Textureless Lambertian Surface?

Cited by 58 publications

References 13 publications

Image Blending in a High Frame Rate FPGA-based Multi-Camera System

Image Blending in a High Frame Rate FPGA-based Multi-Camera System

Real-time implementation of Gaussian image blending in a spherical light field camera

Priors for Large Photo Collections and What They Reveal about Cameras

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