Geometric Calibration Of A Stereo Camera
Geometric Calibration Of A Stereo Camera
Introduction
Modern technology has made cameras smarter and smarter over the past several decades, as they offer better and better image quality as well as photo capturing experiences. Stereo cameras have gained much attention because they provide the visual experience closest to that from human eyes. In this project, we take a closer look at the geometric calibration steps of stereo cameras, evaluate the results obtained from both simulations and real camera experiment, and discuss the features and tradeoffs in the calibration process.
Background
JEDEYE
Stereo cameras use two sets of lenses and imaging sensors to capture a pair of two images each time, emulating the binocular visual system of a human being. These images contain 3D depth information as well as the color contend found in regular camera pictures. Such cameras have only been used in the filming industry and highly advanced research fields so far, very few products are available to replace a regular phone camera or more advanced DSLR’s. JEDEYE stereo camera from Fengyun Vision is a new product to solve this problem integrating advanced electronics and stereo cameras. However, a stereo camera needs to be geometrically calibrated first in order to use in an everyday scenario. Geometric calibration
Geometric camera calibration is the process of estimating the extrinsic and intrinsic parameters of the lens and imaging sensor of a image recording device. These parameters are crucial in correcting lens distortion, depth estimation, 3D scene reconstruction, as well as object measurements. The photo capturing process can be modeled as a transform from 3D world coordinate system to the 2D image coordinates [1]:
W[x y 1]=[X Y Z 1]P
Where the real world coordinates [X Y Z 1] is projected onto the image coordinates [x y 1]. W is a scaling factor for the image, and P is the camera parameter matrix:
P=[R | t] K
[R | t] is the extrinsic matrix, it describes the 3D spatial relationship between the filming object and the camera. It is a 3x3 rotation matrix (R) concatenating with a 3x1 translation vector (t), making a 3x4 matrix. This matrix represents the location of the camera in the 3D scene, as well as the direction it is looking at. It provides rigid transformation from the 3D real world coordinates to the 3D camera’s coordinates. The Intrinsic parameters K characterizes the geometric parameters of the camera including focal length, optical center, and skew coefficient. This matrix then projects the 3D camera coordinates into the image 2D coordinates. The complete image capturing process has two transformation steps, as illustrated in fig. 1.
Part I
Part II
Appendix
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