Abstract
This paper summarized the research status, imaging model, systems calibration, distortion correction, and panoramic expansion of panoramic vision systems, pointed out the existing problems and put forward the prospect of future research. According to the research status of panoramic vision systems, a panoramic vision system with single viewpoint of refraction and reflection is designed. The systems had the characteristics of fast acquisition, low manufacturing cost, fixed single-view imaging, integrated imaging, and automatic switching depth of field. Based on these systems, an improved nonlinear optimization polynomial fitting method is proposed to calibrate the monocular HOVS, and the binocular HOVS is calibrated with the Aruco label. This method not only improves the robustness of the calibration results, but also simplifies the calibration process. Finally, a real-time method of panoramic map of multi-function vehicle based on vcam is proposed.
Highlights
The key technologies of unmanned systems can be divided into four parts [1]: environment perception, precise positioning technology, decision making and planning, and control and execution technology
The HOVS proposed in this paper includes two single-viewpoint variable-scale hyperbolic mirror panoramic vision subsystems with the same configuration and two industrial computers, one of which is used to receive the image data collected by the panoramic vision systems in real time, and the other is used for real-time processing of image data, the data transmission between the two industrial computers is in the form of a 10 Gigabit network cable, and the two single-view variable-scale hyperboloid mirror panoramic vision systems respectively communicate with the industrial computer through a dual-channel gigabit network cable
The panoramic image expansion algorithm is mainly divided into three parts: The first part: As shown in Algorithm 2 below, the mathematical model of panoramic vision systems is established, and the two-dimensional image points on the panoramic image are transformed into three-dimensional world point cloud through the mathematical model of panoramic vision systems; The second part: As shown in the following Algorithm 3, the virtual camera model is established, and the three-dimensional world point cloud is transformed into a twodimensional virtual vision expansion image through the virtual camera model
Summary
The key technologies of unmanned systems can be divided into four parts [1]: environment perception, precise positioning technology, decision making and planning, and control and execution technology. Panoramic vision systems have the advantages of large field of view, integrated imaging, imaging symmetry, rotation invariance [6], especially in the fields of visual navigation, panoramic vision slam [7], visual odometer, active vision, unmanned systems, space field of taking high-definition panoramic images on the moon, panoramic vision systems monitoring, and underwater detection [8] According to their different components, panoramic vision systems can be divided into pan-tilt rotating panoramic vision systems, fisheye lens panoramic vision systems, multi-camera splicing panoramic vision systems [9], catadioptric panoramic vision systems, and panoramic annular optical vision systems [10]. The single-view hyperboloid catadioptric panoramic vision systems have the advantages of good systems design flexibility, good integrated imaging effect, large field of view, and high performance in real-time imaging, and has been gradually applied in the field of unmanned systems technology
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