A comparative review of camera calibrating methods with accuracy evaluation

Salví, Joaquím; Armangué, Xavier; Batlle, Joan

doi:10.1016/s0031-3203(01)00126-1

Cited by 398 publications

(209 citation statements)

References 29 publications

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“…A standard PC was used for implementing the algorithms. Both camera and video projector were calibrated with a linear pinhole model [3].…”

Section: Resultsmentioning

confidence: 99%

“…Amongst all the ranging techniques [1], stereovision is based on viewing the scene from two or more points of view and then ÿnding correspondences between the di erent images in order to triangulate the 3D position. Triangulation is possible if cameras have been calibrated beforehand [2,3]. However, di culties in ÿnding the correspondences arise, even when taking into account epipolar constraints.…”

Section: Introductionmentioning

confidence: 99%

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Pattern codification strategies in structured light systems

Salví

Pagès

Batlle

2004

Pattern Recognition

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975

491

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Coded structured light is considered one of the most reliable techniques for recovering the surface of objects. This technique is based on projecting a light pattern and viewing the illuminated scene from one or more points of view. Since the pattern is coded, correspondences between image points and points of the projected pattern can be easily found. The decoded points can be triangulated and 3D information is obtained. We present an overview of the existing techniques, as well as a new and deÿnitive classiÿcation of patterns for structured light sensors. We have implemented a set of representative techniques in this ÿeld and present some comparative results. The advantages and constraints of the di erent patterns are also discussed.

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“…A standard PC was used for implementing the algorithms. Both camera and video projector were calibrated with a linear pinhole model [3].…”

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Pattern codification strategies in structured light systems

Salví

Pagès

Batlle

2004

Pattern Recognition

Self Cite

975

491

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“…The role of parameter estimation algorithm is to accurately evaluate these parameters, since most of them involve optical characteristics and therefore cannot be measured directly. Tailored for the support of the proposed mathematical model, the parameter estimation algorithm we used can be divided into two parts, camera calibration algorithm [8][9] and the estimation of the projection center's position for the projector. We use algorithms described in Ref.…”

Section: Algorithm For Construction Of Point Cloudmentioning

confidence: 99%

Algorithms for Constructing 3-D Point Clouds Using Multiple Digital Fringe Projection Patterns

Peng

Gupta

Lau³

2005

Computer-Aided Design and Applications

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This paper describes algorithms for generating 3-D point clouds from a set of digital images obtained from projecting phase-shifted sinusoidal fringe patterns onto object. In this paper, a mathematical model is introduced for describing the geometric relationship between the fringe patterns being projected, the image captured and the shape of the object being measured. This model allows considerable flexibility in the spatial configuration of shape measurement system. The algorithms for point cloud construction described in this paper present an improvement over the existing algorithms in terms of accuracy, ease of system calibration, and sensitivity to parameter errors. These algorithms have been incorporated in a shape measurement system and shown to have a very good performance.Keywords: 3-D shape measurement, fringe projection, point cloud generation, triangulation. INTRODUCTIONMany industrial applications require accurate and rapid measurement of the 3-D shapes of objects. Representative applications of 3-D shape measurement include reverse engineering, 3D replication, inspection and quality control. In most of these applications, users need to construct 3D point clouds that correspond to the objects surface by performing measurement on the objects surfaces. Manufacturing industry needs a fast inspection process that can measure and analyze various 3D features on the part and determine if a feature is within the tolerance specifications or not. The measurement scheme needs to be adequately accurate to eliminate measurement errors. Measurement errors can lead to erroneous inspection that results in an acceptable part being rejected and a defective part being accepted. Hence, both inspection speed and accuracy are equally important. Coordinate measurement machines and laser based measurement techniques usually provide very accurate measurements. However, these techniques are slow because they measure various points on the part sequentially. On the other hand, camera-based techniques are usually very fast. Therefore, a possible way to perform the 3D inspection is to use digital cameras to construct a dense point cloud (e.g., points spaced less then 0.25mm apart) corresponding to the part being inspected and then analyze the point cloud to determine if it meets the tolerance specifications. But accuracy associated with the conventional camera-based inspection techniques has not been very high in the area of measurement of geometrically complex 3D shapes. Shape measurement based on digital fringe projection (SMDFP) is a technique for non-contact shape measurement. Due to its fast speed, flexibility, low cost and potentially high accuracy, SMDFP has shown great promise in 3-D shape measurement, especially for applications that require acquisition of dense point clouds. A typical SMDFP system contains one projection unit and one or more cameras (a schematic of a SMDFP system with one projector and one camera is shown in Fig. 1). During the shape measurement process, a set of fringe patterns, whose structur...

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“…Linear least-square techniques for calibration are improved upon by Tsai (1987) and Weng et al (1992), who concentrate on improving the calibration accuracy by comprehensively modelling lens distortion and further iteratively optimising the parameters. A comparative study is presented in Salvi et al (2002). Planar calibration techniques have been proposed by Strum and Maybank (1999) and Zhang (2000) that place the world coordinate system on the calibration object and thus require only arbitrarily scaled 2D coordinates.…”

Section: Introductionmentioning

confidence: 99%

Which pattern? Biasing aspects of planar calibration patterns and detection methods

Mallon

Whelan

2007

Pattern Recognition Letters

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This paper provides a comparative study on the use of planar patterns in the generation of control points for camera calibration. This is an important but often neglected aspect in camera calibration. Two popular checkerboard and circular dot patterns are each examined with two detection strategies for invariance to the potential bias from projective transformations and nonlinear distortions. It is theoretically and experimentally shown that circular patterns can potentially be affected by both biasing sources. Guidelines are given to control such bias. In contrast, appropriate checkerboard detection is shown to be bias free. The findings have important implications for camera calibration, indicating that well accepted methods may give poorer results than necessary if applied naively.

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A comparative review of camera calibrating methods with accuracy evaluation

Cited by 398 publications

References 29 publications

Pattern codification strategies in structured light systems

Pattern codification strategies in structured light systems

Algorithms for Constructing 3-D Point Clouds Using Multiple Digital Fringe Projection Patterns

Which pattern? Biasing aspects of planar calibration patterns and detection methods

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