Single View Point Omnidirectional Camera Calibration from Planar Grids

Mei, Christopher; Rives, Patrick

doi:10.1109/robot.2007.364084

Cited by 347 publications

(341 citation statements)

References 12 publications

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“…Barreto and Araújo proposed a modified version of this model and used it to study various geometric properties, especially those related to line images and their application for calibration [25,28,29]. Mei and Rives proposed to extend the model by adding classical terms for radial and tangential distortion [339].…”

Section: Global Camera Models 55mentioning

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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Section: Global Camera Models 55mentioning

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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“…For the omnidirectional camera, we use the sphere camera model [19] which is able to cover both catadioptric (mirrored) omnidirectional cameras and fisheye cameras. There are a few calibration methods proposed for the calibration using the sphere model [20,21], we preferred to employ [20] since a MATLAB toolbox is provided.…”

Section: Intrinsic Calibrationmentioning

confidence: 99%

A simplified two-view geometry based external calibration method for omnidirectional and PTZ camera pairs

Baştanlar

2016

Pattern Recognition Letters

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a b s t r a c tThe external calibration of a camera system is essential for most of the applications that involve an omnidirectional and a pan-tilt-zoom (PTZ) camera. The methods in the literature fall into two major categories; (1) a complete external calibration of the system which allows all degrees of freedom but highly time consuming, (2) spatial mapping between the pixel coordinates in omnidirectional camera and pan/tilt angles of the PTZ camera instead of explicitly computing the rotation and translation. Most methods in this category make restrictive assumptions about the camera setup such as optical axes of the cameras coincide. We propose an external calibration method that is effective and practical. Using the two-view geometry principles and making reasonable assumptions about the camera setup, calibration is performed with just two scene points. We extract rotation using the point correspondences in images. Locating the PTZ camera in the omnidirectional image is used to find the translation parameters and the real distance between the two scene points lets us compute the translation in correct scale. Results of the simulated and real image experiments show that our method works effectively in real world cases and its accuracy is comparable to the state-of-the-art methods.

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“…There are several methods to perform sphere camera model calibration [19,21]. We used [19] since a MATLAB toolbox is provided with it.…”

Section: Sphere Camera Modelmentioning

confidence: 99%

“…We used [19] since a MATLAB toolbox is provided with it. In our experiments, we used a para-catadioptric camera (ξ = 1).…”

Section: Sphere Camera Modelmentioning

confidence: 99%

A direct approach for object detection with catadioptric omnidirectional cameras

Cinaroglu

Baştanlar

2015

SIViP

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In this paper, we present an omnidirectional vision-based method for object detection. We first adopt the conventional camera approach that uses sliding windows and histogram of oriented gradients (HOG) features. Then, we describe how the feature extraction step of the conventional approach should be modified for a theoretically correct and effective use in omnidirectional cameras. Main steps are modification of gradient magnitudes using Riemannian metric and conversion of gradient orientations to form an omnidirectional sliding window. In this way, we perform object detection directly on the omnidirectional images without converting them to panoramic or perspective images. Our experiments, with synthetic and real images, compare the proposed approach with regular (unmodified) HOG computation on both omnidirectional and panoramic images. Results show that the proposed approach should be preferred. Keywords Catadioptric omnidirectional cameras · Object detection · Human detection · Car detection · Vehicle detectionElectronic supplementary material The online version of this article

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Single View Point Omnidirectional Camera Calibration from Planar Grids

Cited by 347 publications

References 12 publications

Camera Models and Fundamental Concepts Used in Geometric Computer Vision

Camera Models and Fundamental Concepts Used in Geometric Computer Vision

A simplified two-view geometry based external calibration method for omnidirectional and PTZ camera pairs

A direct approach for object detection with catadioptric omnidirectional cameras

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