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Moving object tracking method and device

A technology for moving objects and tracking devices, which is applied to the field of tracking methods and devices for moving objects, can solve the problem of inability to estimate the pose of a target object, and achieve the effects of improving system robustness and accuracy.

Active Publication Date: 2019-09-06
HUAWEI TECH CO LTD
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Problems solved by technology

However, MSCKF can only estimate its own pose, but cannot estimate the pose of the moving target object in the surrounding environment.

Method used

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  • Moving object tracking method and device
  • Moving object tracking method and device

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Embodiment Construction

[0100] The technical solution in this application will be described below with reference to the accompanying drawings.

[0101] MSCKF is a Kalman filter based on multi-state constraints. Multi-state constraints refer to adding the camera poses of multiple frames of images to the Kalman state vector, and performing least squares optimization through the constraints between multiple frames of images before Kalman gain to estimate the spatial position of the feature points, and then according to the optimization The spatial position of the later feature points is used to constrain the state vector. Among them, the multi-frame images are saved in a time-ordered sliding window sequence, and the coordinates of multiple feature points in the multi-frame images are tracked, so as to establish the constraints between the image poses of each frame. Another constraint is that there is a known constraint between the camera pose and the IMU pose at the same moment, and this constraint is ...

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Abstract

The invention provides a moving object tracking method and device. The moving object tracking method comprises the steps: acquiring a current frame collected by a camera; predicting a current state vector of the camera according to an inertial measurement unit (IMU) and the current frame to obtain a predicted value of the current state vector of the camera; predicting a current state vector of a target object in a moving state in the current frame to obtain a predicted value of the current state vector of the target object; and updating the Kalman state vector according to the measurement result of the image feature in the current frame. According to the technical scheme, the target object in the moving state in the surrounding environment can be tracked and the pose of the target object can be estimated while the pose of the target object can be estimated.

Description

technical field [0001] The present application relates to the technical field of pose estimation, and more specifically, to a method and device for tracking a moving object. Background technique [0002] Computer vision is an integral part of various intelligent / autonomous systems in various application fields such as manufacturing, inspection, document analysis, medical diagnosis, and military. What we need is the knowledge of the data and information of the subject being photographed. To put it figuratively, it is to install eyes (cameras / video cameras) and brains (algorithms) on computers to replace human eyes to identify, track and measure targets, so that computers can perceive the environment. Because perception can be thought of as extracting information from sensory signals, computer vision can also be thought of as the science of how to make artificial systems "perceive" from images or multidimensional data. In general, computer vision is to use various imaging sy...

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Application Information

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IPC IPC(8): G06T7/246G06T7/277
CPCG06T7/246G06T7/277G06T2207/20024G06T2207/30244G06T2207/30252G06V10/25G06V20/58G06V10/806G06V10/62G06V20/56
Inventor 李晚龙李学士高亚军温丰
Owner HUAWEI TECH CO LTD
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