Environment object tracking method and device, computer equipment and storage medium
An object tracking and environment technology, applied in computing, image data processing, instruments, etc., can solve problems such as affecting the accuracy of motion tracking, low tracking accuracy, and poor motion tracking effect.
Active Publication Date: 2019-05-03
INST OF INTELLIGENT MFG GUANGDONG ACAD OF SCI
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[0003] However, the existing visual-inertial odometry provides environmental object tracking methods that only use point features in the visual image when using visual data for motion tracking. The tracking effect is not good; at the same time, when the number of point features is large, the calculation burden of the system will be large, which will also affect the accuracy of motion tracking
[0004] Therefore, the existing environmental object tracking methods have the problem of low tracking accuracy
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[0059]In order to make the purpose, technical solution and advantages of the present application clearer, the present application 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 application, and are not intended to limit the present application.
[0060] In one embodiment, such as figure 1 As shown, an environmental object tracking method is provided, which includes the following steps:
[0061] Step 210, acquire the environment object image, and extract object point features and object line features in the environment object image.
[0062] Wherein, the environmental object image may refer to an image with an external environment. In practical applications, the external environment can be photographed by a camera to obtain an environmental object image, and the environmental object image includes a tracking object...
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The invention relates to an environment object tracking method and device, computer equipment and a storage medium. The method comprises the steps that an environment object image is acquired, and object point features and object line features are extracted from the environment object image; the number of the point features and the number of the line features are counted; a point feature weight and a line feature weight are determined according to the number of the point features; according to the point feature weight and the line feature weight, weighted adjustment is performed on the point feature number and the line feature number to obtain a weighted point feature number and a weighted line feature number; target point characteristics conforming to the number of the weighted point characteristics is extracted from the object point characteristics, and target line characteristics conforming to the number of the weighted line characteristics are extracted from the object line characteristics; and an environment object according to the target point feature and the target line feature is tracked. By adopting the method, the motion tracking accuracy can be improved.
Description
technical field [0001] The present application relates to the technical field of motion tracking, and in particular to an environmental object tracking method, device, computer equipment and storage medium. Background technique [0002] Visual-inertial odometry (visual-inertial odometry, VIO) is an algorithm that fuses visual data and inertial measurement unit (Inertial measurement unit, IMU) data to achieve simultaneous localization and mapping (SLAM). While visual-inertial odometry uses visual data for motion tracking, it fuses inertial measurement unit data to improve the performance of motion tracking. It is a low-cost, high-performance motion tracking algorithm. Therefore, visual-inertial odometry is often used in the fields of automobile automatic driving, virtual augmentation technology, augmented reality technology and robot navigation. [0003] However, the existing visual-inertial odometry provides environmental object tracking methods that only use point features...
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Inventor 苏泽荣周雪峰范杰轩
Owner INST OF INTELLIGENT MFG GUANGDONG ACAD OF SCI