基于快速多尺度估计的重新检测目标跟踪算法

胡昭华; 黄嘉净

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基于快速多尺度估计的重新检测目标跟踪算法

更新时间：2026-09-04

- 基于快速多尺度估计的重新检测目标跟踪算法
- A re-detection object tracking algorithm based on fast multi-scale estimation
- 微电子学与计算机 2020年37卷第9期页码：11-17
- 作者机构：
  
  1. 南京信息工程大学机构电子与信息工程学院,江苏,南京,210044
  2. 南京信息工程大学江苏省大气环境与装备技术协同创新中心,江苏,南京,210044
- 作者简介：
- 基金信息：
  
  国家自然科学基金 61601230江苏省自然科学基金 BK20141004
- DOI：
  中图分类号：
- 纸质出版：2020
- 稿件说明：
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胡昭华, 黄嘉净. 基于快速多尺度估计的重新检测目标跟踪算法[J]. 微电子学与计算机, 2020, 37(9): 11-17.

HU Zhao-hua, HUANG Jia-jing. A re-detection object tracking algorithm based on fast multi-scale estimation[J]. 2020, 37(9): 11-17.
胡昭华, 黄嘉净. 基于快速多尺度估计的重新检测目标跟踪算法[J]. 微电子学与计算机, 2020, 37(9): 11-17. DOI：

HU Zhao-hua, HUANG Jia-jing. A re-detection object tracking algorithm based on fast multi-scale estimation[J]. 2020, 37(9): 11-17. DOI：

摘要

为了解决跟踪过程中的漂移问题，本文提出了一种基于快速多尺度估计的重新检测目标跟踪算法。在跟踪过程中，跟踪器通过目标的最大响应值确定目标的位置，并且通过一个新的自适应检测指标检测当前位置的可靠性.不同于其他检测指标的是，新的检测指标减少了对最大响应值的依赖.若检测出当前帧的位置不可靠，我们的方法可以通过Edge boxes方法产生一系列的目标候选框，并通过非极大值抑制方法和欧几里德度量方法选出最优目标位置.此外，我们提出了自适应更新的方法来减少由于跟踪失败导致的误差.实验结果表明，本文提出的算法在精确度和成功率方面都有很好的效果.

Abstract

To solve the problem of drift in the tracking

in this paper

a re-detection object tracking algorithm based on fast multi-scale estimation is proposed. In the tracking process

the tracker locates the target position through the maximum value of the response and detects the reliability of the current position using a new self-adaptive detection criterion. In contrast to other detection criteria

our new detection criterion reduces the dependence on the maximum response value. If the current location is determined to be unreliable

our method can generate target candidate boxes by using the edge boxes algorithm and select the best target location by applying the non-maximum suppression (NMS) and the Euclidean metric methods. Furthermore

we proposed an adaptive updating method to reduce the errors caused by tracking failure. Experimental results show that our approach has a good performance in terms of precision and success rates.

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references

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