Pure rotation camera self-calibration method based on spherical projection model

A technology for rotating cameras and cameras, which can be used in image analysis, image data processing, instruments, etc., and can solve problems such as complex matrix numerical operations

Active Publication Date: 2013-01-02
NANKAI UNIV
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Problems solved by technology

Therefore, it avoids the problem that the existing self-calibration method requires complex matrix numerical operations, and only needs 4 matching points on

Method used

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  • Pure rotation camera self-calibration method based on spherical projection model
  • Pure rotation camera self-calibration method based on spherical projection model
  • Pure rotation camera self-calibration method based on spherical projection model

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Experimental program
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Embodiment 1

[0135] First, construct the spherical projection model of the pinhole camera

[0136] Define point P i , P j represent the i and j spatial points respectively. The abscissa axis and the ordinate axis of the pixel coordinate system are denoted by u and v respectively. by Indicates the camera coordinate system, where The origin of is at the optical center of the camera, The z-axis coincides with the optical axis of the camera, the x-axis direction is the same as the u-axis direction, and the y-axis direction is the same as the v-axis direction. f is the focal length of the camera, and the unit of f is meter; cp i , cp j represents the point P i , P j The corresponding image pixels are in down position. expressed by The unit virtual sphere whose origin is the center of the sphere; s i ,s j cp respectively i , cp j corresponding to The projection point on is called spherical projection point;

[0137] For a camera in pure rotational motion, and Respect...

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Abstract

The invention discloses a novel pure rotation self-calibration method based on a spherical projection model, aims at internal parameter calibration tasks of a pinhole camera, and particularly relates to a pure rotation camera self-calibration method based on the spherical projection model. A spherical projection model of the pinhole camera is constructed, and that the distance between a space stationary point and a corresponding spherical projection point is consistent during pure rotation of the camera is analyzed; a constrain equation set of internal parameters is constructed according to the property; and the equation set is solved by a nonlinear least square algorithm. Compared with prior methods, internal parameters can be obtained by using corresponding point characteristics on two images, complicated matrix numeric calculation is not needed, only four matching points on the two images can complete calibration of four internal parameters of the camera, and the method is suitable for on-line and off-line calibration. Simulation and experiment results show that the method is simple and practical, high in calibration accuracy and good in robustness for image noise and translation noise.

Description

technical field [0001] The invention belongs to the technical field of computer vision and camera calibration, in particular to a self-calibration method for a purely rotating camera based on a spherical projection model. Background technique [0002] The calibration of the internal parameters of the camera refers to the process of obtaining them. It is one of the classic problems in computer vision, and it is also an important technology for the control system based on visual feedback. Camera calibration methods can be roughly divided into traditional calibration methods and self-calibration methods. Traditional calibration methods are represented by Tsai's three-dimensional calibration block calibration method [1] and Zhang Zhengyou's planar calibration method [2]. The traditional methods have high calibration accuracy, but they are all offline methods and require high-precision calibration blocks and other devices. The self-calibration method was proposed by Faugeras [3]...

Claims

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Application Information

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IPC IPC(8): G06T7/00
Inventor 方勇纯李宝全张雪波刘开征
Owner NANKAI UNIV
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