Method and device for tracking mixing features

A tracking device and mixed feature technology, applied in the field of computer vision, can solve problems such as inability to guarantee tracking stability, inability to automatically retrieve feature points, and inability to guarantee stability

Inactive Publication Date: 2012-12-12
ZTE CORP +1
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AI Technical Summary

Problems solved by technology

[0005] The above-mentioned SIFT algorithm can obtain stable matching points, but its operation efficiency is low, and it is difficult to apply in real-time systems. Although the KLT tracking algorithm c

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  • Method and device for tracking mixing features

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Embodiment Construction

[0033] The basic idea of ​​the present invention is: according to the SIFT algorithm, the key frame image is extracted and saved; the KLT tracking algorithm thread is used to track the feature point of the key frame image according to the KLT tracking algorithm, and the feature point of the current frame image is obtained, and the calculation unit After the response matrix is ​​successful, check whether the number of feature points in the current frame image is sufficient for the next tracking. When the number of feature points is insufficient, notify the SIFT algorithm thread; the SIFT algorithm thread performs feature point extraction and matching according to the notification of the KLT tracking algorithm thread. And return the matched feature points to the KLT tracking algorithm thread; the KLT tracking algorithm thread integrates the received feature points returned by the SIFT algorithm thread into the tracked feature points retained by itself for tracking.

[0034] The p...

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Abstract

The invention discloses a method for tracking mixing features. Feature points of key frame images are extracted and saved by SIFT (scale-invariant feature transform) algorithm. A KLT (Kanade-Lucas-Tomasi feature tracker) algorithm thread tracks the feature points of the key frame images by KLT algorithm to obtain the feature points of current frame images, detects whether number of the feature points is sufficient or not for the next tracking after homography is successfully calculated, and notifies a SIFT algorithm thread when the feature points are insufficient. The SIFT algorithm thread extracts and matches the feature points according to the notice given by the KLT algorithm thread, and returns the matched feature points to the KLT algorithm thread. The KLT algorithm thread blends the received feature points returned by the SIFT algorithm thread into tracking feature points remained in the KLT algorithm thread for tracking. The invention further discloses a device for tracking mixing features. By the method and the device, stable tracking is achieved. The method and the device are applicable to camera tracking fields such as virtual studios and virtual sports.

Description

technical field [0001] The invention relates to computer vision technology, in particular to a tracking method and device for mixed features. Background technique [0002] In computer vision technology, the stability and real-time performance of camera tracking are the most challenging problems. Generally speaking, the entire tracking system can be divided into two types: matching type and tracking type. The matching tracking process includes three parts: feature point extraction, feature point matching, and camera pose calculation; the tracking track process includes: feature point extraction, feature point tracking, and camera pose calculation. [0003] In the matching scheme, the scale-invariant feature transform (SIFT) algorithm proposed by David Lowe in 2004 is a typical representative. The SIFT algorithm requires first taking an image as a key frame, using the DoG algorithm to extract a certain number of feature points from the key frame, and then using a method of m...

Claims

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Application Information

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IPC IPC(8): G06T7/20
Inventor 王涌天刘伟刘越杨健王高浩
Owner ZTE CORP
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