A Novel Camera Calibration Pattern Robust to Incomplete Pattern Projection

This paper addresses the problem of highly accurate, highly speedy, more reliable and fully automatic camera calibration. Our objective is to construct a reliable and fully automatic system to supply a more robust and highly accurate calibration scheme. A checkerboard pattern is used as calibration pattern. After the corner points on image are detected, an improved Delaunay triangulation based algorithm is used to make correspondences between corner points on image and corner points on checkerboard in 3D space. In order to determine precise position of the actual corner points, a geometrical constraint based global curve fitting algorithm has been developed. The experimental results show that the geometrical constraint based method can improve remarkably the performance of the feature detection and camera calibration.

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A Rotation Based Sorting Method for the Feature Points Abstracted from Skew Calibration Image

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.427-429.1939 ◽

2013 ◽

Vol 427-429 ◽

pp. 1939-1943 ◽

Cited By ~ 1

Author(s):

Qian Bian ◽

Sui Yang Chen ◽

Yang Chuan Liu

Keyword(s):

Camera Calibration ◽

Feature Points ◽

Skew Angle ◽

Sorting Method ◽

Calibration Pattern ◽

Calibration Accuracy ◽

Skew Angles

During camera calibration, the calibration pattern image is always skew. This brings much difficult to feature points sorting, which affects calibration accuracy. In this study, a rotation based sorting method is proposed. First, detect the skew angle accurately; then, transform the original coordinates to the rotated coordinates and establish the mapping relation; then, sort the rotated coordinates; finally, sort the original coordinates using the mapping relation. To verify the feasibility of this method, an experiment is carried out. The result shows that the rotation based sorting method can sort the feature points accurately at different skew angles. Its accuracy makes this method suitable for high accurate camera calibration.

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Distance Measurement Using a Stereo Vision System

Solid State Phenomena ◽

10.4028/www.scientific.net/ssp.196.189 ◽

2013 ◽

Vol 196 ◽

pp. 189-197 ◽

Cited By ~ 5

Author(s):

Bogdan Żak ◽

Stanisław Hożyń

Keyword(s):

Camera Calibration ◽

Stereo Vision ◽

Classical Method ◽

Vision System ◽

Distance Measurement ◽

Stereo Vision System ◽

Main Emphasis ◽

Calibration Pattern ◽

Metric Information

In this paper the attempt to make an analysis of distance measurement using a stereo vision system was presented. Main emphasis was placed on the geometric camera calibration. The classical method based on the specially prepared calibration pattern with known dimensions and position in a certain coordinates system was performed. Finally, the metric information obtained from images was presented.

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Projection-Mapping-Based Object Pointing Using a High-Frame-Rate Camera-Projector System

10.21203/rs.3.rs-78087/v1 ◽

2020 ◽

Author(s):

Idaku Ishii ◽

Deepak Kumar ◽

Sushil Raut ◽

Kohei Shimasaki ◽

Taku Senoo

Keyword(s):

Real Time ◽

Camera Calibration ◽

Vision System ◽

Frame Rate ◽

Multiple Objects ◽

Projection Mapping ◽

High Frame Rate ◽

Pattern Projection ◽

Modulated Light

Abstract An informative object pointing method using a spatiotemporal-modulated pattern projection is proposed to recognize and localize pointed objects by using a distantly located high-frame-rate vision system. We developed a prototype for projection-mapping-based object pointing that consists of an AI-camera-enabled projection (AiCP) system used as a transmitter, for informative projection mapping, and an HFR vision system operated as a receiver. The AiCP system detects multiple objects in real time at 30 fps with a CNN-based object detector, and simultaneously encodes and projects the recognition results of the detector as 480-Hz-modulated light patterns on to the objects to be pointed. The multiple 480-fps cameras can directly recognize and track the objects pointed at by the AiCP system without camera calibration or complex recognition methods by decoding the brightness signals of pixels in the images. To demonstrate the eectiveness of our proposed method, several desktop experiments using miniature objects and scenes were conducted under various conditions.

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Do we really need an accurate calibration pattern to achieve a reliable camera calibration?

Computer Vision — ECCV'98 - Lecture Notes in Computer Science ◽

10.1007/bfb0055665 ◽

1998 ◽

pp. 158-174 ◽

Cited By ~ 46

Author(s):

Jean -Marc Lavest ◽

Marc Viala ◽

M. Dhome

Keyword(s):

Camera Calibration ◽

Calibration Pattern

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Common self-polar triangle of separate circles for light field camera calibration

Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University ◽

10.1051/jnwpu/20213930521 ◽

2021 ◽

Vol 39 (3) ◽

pp. 521-528

Author(s):

Qi Zhang ◽

Qing Wang

Keyword(s):

Camera Calibration ◽

Light Field ◽

Linear Optimization ◽

Real Data ◽

Calibration Method ◽

Calibration Algorithm ◽

Calibration Pattern ◽

The Common ◽

Projection Center ◽

Planar Homography

Due to the trade-off between spatial resolution and angular resolution of the light field, it is difficult to extract high precision corner points and line features from light fields for calibration. A novel calibration pattern of separate circles is designed, and a light field camera calibration method based on common self-polar triangle with respect to separate circles is proposed in this paper. First, we explore the uniquity and reconstruction of common self-polar triangle with respect to sperate circles. Then, based on projections of the multi-projection-center model on the plane and conic, the common self-polar triangle on the sub-aperture image is reconstructed and used to estimate planar homography. Finally, a light field camera calibration algorithm is then proposed, including linear initialization and non-linear optimization. Experimental results on both synthetic and real data have verified the effectiveness and robustness of the method and algorithm proposed.

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On the design of a fractal calibration pattern for improved camera calibration

tm - Technisches Messen ◽

10.1515/teme-2017-0013 ◽

2017 ◽

Vol 84 (7-8) ◽

Cited By ~ 1

Author(s):

Hendrik Schilling ◽

Maximilian Diebold ◽

Marcel Gutsche ◽

Bernd Jähne

Keyword(s):

Camera Calibration ◽

Large Range ◽

Ground Truth ◽

High Accuracy ◽

Ground Truth Data ◽

Magnification Factors ◽

Wide Range ◽

Calibration Pattern ◽

Planar Calibration ◽

Very High

AbstractCamera calibration, crucial for computer vision tasks, often relies on planar calibration targets to calibrate the camera parameters. This work describes the design of a planar, fractal, self-identifying calibration pattern, which provides a high density of calibration points for a large range of magnification factors. An evaluation on ground truth data shows that the target provides very high accuracy over a wide range of conditions.

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Efficient and Accurate Camera Calibration Based on Planar Pattern

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.204-210.1258 ◽

2011 ◽

Vol 204-210 ◽

pp. 1258-1261

Author(s):

Dan Xia ◽

De Hua Li ◽

Sheng Yong Xu

Keyword(s):

Camera Calibration ◽

Control Points ◽

Pattern Control ◽

Harris Detector ◽

Calibration Pattern ◽

Planar Pattern ◽

Planar Calibration ◽

Calibration Control

We describe an effective method for calibrating cameras by using planar calibration patterns. The calibration pattern control points are localized by Harris detector incorporating the gradient histogram. The accuracy of the calibration control points location consequently improves the accuracy of the camera calibration. Additionally, optimization computation is carried out for increasing the accuracy of camera calibration results. Experiments using real images verified the effectiveness and robustness of the proposed method.

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