A Fast Multi-Scale Estimation Object Tracking Method on Re-Detection

A re-detection and target tracking technology, which is applied in the fields of image processing and computer vision, can solve problems such as error and slow tracking speed, and achieve the effect of solving fast motion, improving computing speed, and improving feature expression ability
CN110175649BActive Publication Date: 2022-06-07NANJING UNIV OF INFORMATION SCI & TECH
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Patents(China)
Current Assignee / Owner
NANJING UNIV OF INFORMATION SCI & TECH
Publication Date
2022-06-07

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Abstract

The present invention proposes a fast multi-scale estimation target tracking algorithm on deep features and re-detection. The characteristics of the target are represented by the method of deep learning, which improves the feature expression ability of the target. In the tracking stage, when extracting features of image blocks of different scales, PCA dimensionality reduction can reduce the amount of calculation and improve the overall calculation speed. Based on two discriminant indicators, peak side lobe ratio (PSR) and confidence smoothing constraint (SCCM), a new detection index is proposed, so that the tracking reliability of the current frame can be measured more accurately. If the reliability of the current frame is low, a series of target candidate boxes are generated by the method of Edgeboxes for re-detection.
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Description

technical field

[0001] The invention belongs to the fields of image processing and computer vision, and uses a deep learning method to learn target features, and realizes accurate tracking of the target by re-detecting when the target drifts. It can be used in areas such as unmanned driving and video surveillance. Background technique

[0002] Object tracking is a key problem in computer vision, and has a wide range of applications in various fields such as video surveillance, behavior recognition, unmanned driving, and medical images. The purpose of target tracking is to estimate the target position for each subsequent frame given the initial position of the target in the first frame. At present, the main computer vision tracking methods mainly include the tracking method based on correlation filtering and the tracking method based on deep learning.

[0003] Target tracking algorithms based on correlation filtering have developed rapidly since 2010, among which Henriques ...

Claims

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