Timestamp delay calibration method and system, equipment and computer readable storage medium

A calibration method and calibration system technology, applied in the field of time stamp delay calibration of video and inertial data, and computer readable storage media, can solve the problems of easy system crash, time stamp synchronization, and lack of universality of the method, and achieve great versatility performance, and the effect of improving accuracy

Pending Publication Date: 2022-02-11
SHICHEN INFORMATION TECH SHANGHAI CO LTD
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  • Application Information

AI Technical Summary

Problems solved by technology

[0002] In computer vision systems, visual inertial odometry using cameras and inertial measurement units (Inertial Measurement Unit, IMU) has achieved good results in recent years. Video data can be obtained by using cameras, and inertial data can be obtained by using IMUs. Because vision (i.e., video data) and IMU information (i.e., inertial data) have complementary characteristics. These methods of merging visual and inertial information for pose estimation generally require strict alignment of time stamps between video and inertial data, otherwise it will not only affect the system’s precision, but also makes the system extremely vulnerable to crashes
[0003] However, many current devices that provide both video and inertial data, such as smartphones, GoPro action cameras, insta360 panoramic cameras, etc., do not use hardware to synchronize the time stamps of video and inertial data, so there may be a certain gap between the two. Delay, and this delay is not a fixed value, but will change every time the data is collected, so it is impossible to know the delay of a certain collection of data through prior calibration
For GoPro sports cameras and insta360 panoramic cameras, the delay may reach tens of milliseconds or even hundreds of milliseconds. Under such a large delay, the Visual-Inertial Odometry (VIO) based on video and inertial data ) has been unable to operate normally, and online delay calibration is required
[0004] At present, the existing visual and inertial time-lapse calibration methods are mainly divided into two types: offline calibration and online calibration. Offline calibration requires the use of special equipment such as calibration boards and professional acquisition methods to perform calibration, resulting in high positioning costs. , the positioning program is more complicated, and it is difficult to use in the above-mentioned online use or the scene that changes every time, the application scene is relatively limited, and the method is not universal. In addition, the online calibration is mainly through the use of EKF algorithm or nonlinear Optimizing online optimization requires a relatively good initial value, or the delay of visual and inertial data is small, so that the vio algorithm can barely run, and the positioning accuracy is not high, so how to design a universal positioning method and Improving positioning accuracy has always been an urgent problem in the industry.

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  • Timestamp delay calibration method and system, equipment and computer readable storage medium
  • Timestamp delay calibration method and system, equipment and computer readable storage medium
  • Timestamp delay calibration method and system, equipment and computer readable storage medium

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Embodiment Construction

[0055] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0056] A method for calibrating the time stamp delay of video and inertial data provided by the present invention will be described in detail below.

[0057] see figure 1 , is a schematic flowchart of a method for calibrating time delays of video and inertial data timestamps in an embodiment of the present invention.

[0058] In step S1, step 1, calculate the relative corners between all adjacent frames in the video data to obtain a first sequence, each value in the first sequence represents the size of the relative corners between adjacent frames.

[0059] In this embodiment, the first sequence ...

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Abstract

The invention provides a video and inertial data timestamp delay calibration method and system, equipment and a computer readable storage medium, and the method comprises the steps: calculating a relative rotation angle between all adjacent frames in video data to obtain a first sequence, and each value in the first sequence represents the size of the relative rotation angle between the adjacent frames; integrating the rotation component of the inertial data according to the time interval of adjacent frames in the video data to obtain a second sequence; calculating a cross correlation coefficient of the first sequence and the second sequence; and determining the timestamp delay between the video and the inertial data by using the cross correlation coefficient. According to the method provided by the invention, only relative rotation between two adjacent frames of images in the video data and the angular acceleration data in the inertial data are used, so that on one hand, the maximum universality of the method is achieved by using least data; and on the other hand, the calibration precision can be greatly improved by using cross-correlation analysis and phase correlation analysis calculation.

Description

technical field [0001] The invention relates to the field of computer vision, in particular to a method, system, device and computer-readable storage medium for time stamp delay calibration of video and inertial data. Background technique [0002] In computer vision systems, visual inertial odometry using cameras and inertial measurement units (Inertial Measurement Unit, IMU) has achieved good results in recent years. Video data can be obtained by using cameras, and inertial data can be obtained by using IMUs. Because vision (i.e., video data) and IMU information (i.e., inertial data) have complementary characteristics. These methods of merging visual and inertial information for pose estimation generally require strict alignment of time stamps between video and inertial data, otherwise it will not only affect the system’s Accuracy, but also makes the system extremely vulnerable to crashes. [0003] However, many current devices that provide both video and inertial data, su...

Claims

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Application Information

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Patent Type & AuthorityApplications(China)
IPC IPC(8): H04N5/262H04N5/95H04N21/236H04N21/434H04N21/8547
CPCH04N21/8547H04N21/23608H04N21/4344H04N5/95H04N5/2628
Inventor曾灿灿顾升宇王强张小军
OwnerSHICHEN INFORMATION TECH SHANGHAI CO LTD