Depth error calibration method for time-of-flight camera
A time-of-flight and error calibration technology, applied in the field of data processing, can solve problems such as non-fixed and random forms, difficult model description and correction, etc.
Pending Publication Date: 2020-09-15
北京深测科技有限公司
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The characteristic of this kind of error is that the form is not fixed and random, it is difficult to establish a unified model to describe and correct this kind of error
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[0039] The application will be further described in detail below with reference to the drawings and embodiments. It can be understood that the specific embodiments described here are only used to explain the related invention, but not to limit the invention. In addition, it should be noted that, for ease of description, only the parts related to the relevant invention are shown in the drawings.
[0040] It should be noted that the embodiments in the application and the features in the embodiments can be combined with each other if there is no conflict. Hereinafter, the present application will be described in detail with reference to the drawings and in conjunction with embodiments.
[0041] The depth error calibration method of a Time Of Flight (TOF) camera of the present invention is used to perform depth value error calibration on the three-dimensional image data or three-dimensional point cloud image data collected and generated by the time of flight camera. figure 1 It is a ...
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The invention provides a depth error calibration method for a time-of-flight camera, and the depth error calibration method comprises the steps: extracting original image data through a processor, andobtaining depth image data from the original image data; obtaining a preset training set constructed by the processor; determining a first penalty coefficient and a first Gaussian kernel parameter ofa preset least square support vector machine algorithm according to a preset training set; according to the first penalty coefficient and the first Gaussian kernel parameter, calling a preset least square support vector machine algorithm to train the preset training set to obtain a nonlinear depth calibration model corresponding to the preset training set; taking a depth value corresponding to each pixel of the depth image data as input data of a nonlinear depth calibration model; obtaining a depth error value corresponding to each pixel of the depth image data according to the output data ofthe nonlinear depth calibration model; and obtaining calibrated depth image data according to the depth error value corresponding to each pixel and the depth image data.
Description
Technical field [0001] The invention relates to the field of data processing, in particular to a depth error calibration method for a time-of-flight camera. Background technique [0002] Time Of Flight (TOF) cameras are a technology that has developed rapidly in recent years. It is a 3D imaging sensor that provides depth images and amplitude images at a high frame rate. As TOF cameras are limited by imaging conditions and external environment, the data captured by them will always have certain errors. [0003] TOF camera errors can be divided into two categories: systematic errors and non-systematic errors. System errors are not only triggered by their inherent properties, but also by the imaging conditions of the camera system. The main feature of such errors is that their forms are relatively fixed. These errors can be evaluated in advance, and the correction process is relatively convenient. Non-systematic errors are errors caused by external environment and noise. The chara...
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IPC IPC(8): G06T7/593G06T7/80G06T5/00
CPCG06T7/593G06T7/85G06T2207/10028G06T2207/20081G06T5/70
Inventor 朱翔
Owner 北京深测科技有限公司