DocumentCode :
3611282
Title :
Camera calibration and pose estimation from planes
Author :
Bazargani, Hamid ; Laganiere, Robert
Author_Institution :
Univ. of Ottawa, Ottawa, ON, Canada
Volume :
18
Issue :
6
fYear :
2015
fDate :
12/1/2015 12:00:00 AM
Firstpage :
20
Lastpage :
27
Abstract :
Camera calibration plays a key role in every computer vision application dealing with the problems of recovering a camera´s geometry with respect to a 3D world reference, making 3D measurement in a captured scene or extracting 3D data from observed objects. These problems emerge in various applications such as structure from motion, robotics, augmented reality, 3D object recognition, and Simultaneous Localization And Mapping (SLAM). Using a camera as a measuring device is becoming an important trend [1], and as a consequence the need for calibrating this instrument also becomes of prime importance. Cameras are, by nature, projective devices that map our 3D world onto a 2D image. Their prime use is to create representations (i.e., images) of an environment and its actors as pictured from a particular viewpoint at a precise moment in time. Extracting 3D data from such devices is therefore inherently difficult. The camera measures the intensity of the light emitted or reflected from a certain direction; however, the depth information is lost. The projective process also implies that, in the absence of any external reference, the scale of the observed objects is undeterminable; that is an object of a given size at a given camera distance will produce the same image as an object of twice the size seen at twice the distance. In spite of these limitations, with a good understanding of the camera geometry, 3D reconstruction can become possible under specific circumstances. In this article, we review some techniques proposed in the literature to parameterize camera metric information, also referred to as camera calibration techniques. We also illustrate the use of calibrated cameras by describing two application examples involving camera pose estimation and distance estimation.
Keywords :
calibration; computational geometry; computer vision; computerised instrumentation; distance measurement; image reconstruction; image representation; intensity measurement; optical variables measurement; pose estimation; video cameras; 2D image; 3D measurement; 3D reconstruction; 3D world reference; camera calibration; camera geometry; computer vision application; distance estimation; image representation; light intensity measurement; parameterize camera metric information; pose estimation; projective device; projective process; Calibration; Cameras; Distortion; Lenses; Maximum likelihood estimation; Measurement uncertainty; Three-dimensional displays;
fLanguage :
English
Journal_Title :
Instrumentation Measurement Magazine, IEEE
Publisher :
ieee
ISSN :
1094-6969
Type :
jour
DOI :
10.1109/MIM.2015.7335834
Filename :
7335834
Link To Document :
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