Monocular visual focusing stack acquisition and scene reconstruction method

Abstract

The invention discloses a monocular visual focusing stack acquisition and scene reconstruction method. The method comprises the following steps of: controlling rotation of a prime lens through an electric control rotator, and acquiring focusing stack data; in the rotation process of the prime lens, fixing a detector and synchronously translating the prime lens along an optical axis of a camera; establishing a corresponding relationship between a rotation angle of the electric control rotator and an imaging surface depth according to position adjustment of the prime lens; establishing a corresponding relationship between the rotation angle of the electric control rotator and a focusing object surface depth by combining an object image relationship of lens imaging according to the corresponding relationship between the rotation angle of the electric control rotator and the focusing object surface depth; and functionally calculating a depth of each object point by utilizing maximized focusing measurement according to the corresponding relationship between the rotation angle of the electric control rotator and the focusing object surface depth, and outputting a scene depth map and a full focusing map so as to reconstruct a three-dimensional scene. According to the method, the requirements for three-dimensional scene reconstruction, image depth information and full focusing under field of view (FOV) of the cameras can be satisfied, and depth images ad full focusing images can be generated.

Description

Technical field [0001] The invention relates to the field of computer vision and digital image processing, and is a monocular vision focusing stack collection and scene reconstruction method. Background technique [0002] Image depth refers to the distance between the real scene and the camera imaging plane. Depth information has also been widely used in sensors, such as image recognition and processing, intelligent robots, virtual and reality technologies and so on. [0003] At present, there are two main ways to obtain image depth information, namely, depth camera shooting and depth estimation software estimation. In the depth camera system, the depth acquisition is mostly based on the time-of-flight principle to estimate the depth, but its accuracy is low due to greater environmental influence factors. In addition, there are depth sensing devices based on binocular stereo matching, which have high hardware requirements, complicated algorithms, and long calculation times, which...

AI Technical Summary

Problems solved by technology

In the depth camera system, the acquisition of depth mostly relies on the time-of-flight principle to estimate the depth, but due to the large environmental factors, its accuracy is low

In addition, there is also a depth sensing device based on binocular stereo matching, which has high requirements for hardware, and the algorithm is complex, and the calculation time is long, so it is not suitable for wide use.

For depth estimation software, the accuracy rate is often low in the process of processing data

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