Target tracking and positioning method based on Azure Kinect

Abstract

The invention discloses a target tracking and positioning method based on Azure Kinect. The target tracking and positioning method based on Azure Kinect comprises the following steps: 1, extracting three-dimensional point cloud data of a target object through Azure Kinect; 2, mapping the point cloud of the target object to a color map; 3, establishing a target object'color-shape 'model fused with depth information; 4, acquiring a color image and a depth image in real time; 5, performing connected domain segmentation on the target object and the similar color background by using depth variance; 6, completing the target recognition through the target object shape deviation ratio and the histogram Bhattacharyya distance; 7, if the target is successfully identified, calculating a target substance center P0, and finishing target positioning according to a depth mean value of a target substance center region; 8, outputting the coordinates of the target object, and updating the color histogram, the length and width values and the depth value of the target object; 9, if the target identification fails, repeating the steps 4 to 8. The problem that a target tracking method based on color features is easily interfered by similar color backgrounds can be solved.

Description

technical field [0001] The invention relates to the technical field of computer vision, in particular to an Azure Kinect-based target tracking and positioning method. Background technique [0002] Kinect is a 3D somatosensory camera launched by Microsoft. It has a color camera and a depth sensor. Because Kinect can obtain the depth information of objects, it also shows unique advantages in the field of target tracking. Azure Kinect provides developers with four sensor SDKs for depth, vision, sound, and direction, including a 1-megapixel TOF depth camera, a 12-megapixel RGB high-definition camera, a 7-microphone circular array, and an inertial measurement unit (IMU). A controlled access mode and custom installation that provide cross-platform, low-level access to Azure Kinect device configuration and hardware sensing streams. [0003] The depth camera can choose wide or narrow FOV field of view when controlling access, so the data acquired in the actual space will be more ac...

AI Technical Summary

Problems solved by technology

[0007] At present, most of the target tracking methods using Kinect are based on color features. This tracking method needs to mark the tracking target in advance, which is inconvenient to operate. When the target object and the background color are similar, it is easily interfered by similar colors, and the tracking effect is not ideal.

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