模糊化多视觉信息融合的视觉跟踪策略

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模糊化多视觉信息融合的视觉跟踪策略

更新时间：2025-07-09

- 模糊化多视觉信息融合的视觉跟踪策略
- Issue 8, Pages: 33-37(2009)
- 作者机构：
  
  哈尔滨工业大学机器人技术与系统国家重点实验室
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP391.41
- Online First：10 August 2009，
  
  Published：2009
- 稿件说明：
移动端阅览
[J]. 2009, (8): 33-37.
DOI：

[J]. 2009, (8): 33-37. DOI：

摘要

为了提高视觉跟踪系统在空间环境对外界变化的适应能力

提出一种模糊化多视觉信息融合的视觉跟踪策略.该策略综合了多个反映目标特征的视觉信息

通过对选择的每一项子特征集进行模糊化处理

提高了识别的智能化程度.针对运动物体分割阈值受噪声干扰的问题

提出一种结合人口统计与区域生长的区域分割方法

实现了运动区域特征的稳定聚类.相对于传统的局部特征识别方法

这种多特征融合技术适合应用于复杂的动态环境

冗余信息间的互相补充可确保特征在不确定环境中的识别.试验结果表明

该策略能够实现鲁棒的特征提取和跟踪

尤其当出现被跟踪物体部分遮挡以及外界发生光线变化时

视觉跟踪系统仍能够实现稳定、快速的识别.

Abstract

To improve the adaptability of visual tracking system for various circumstances in space

a visual tracking strategy based on fuzzy multi visual cue integration is proposed

which synthesizes multi visual cue together to represent the features of object. The recognition of object is intelligentized by integration of each fuzzy cue. To deal with the effects of noise on segmentation threshold of moving object

a new region-based segmentation is chosen to realize stable clustering of moving region by integrating population statistics and region growing. Compared with conventional local feature recognition

this strategy is adaptive to complex and dynamic circumstances. Redundant information complements each other for ensuring feature recognition and tracking in uncertain environment. Experimental results demonstrate the robust feature recognition and tracking with this strategy

especially in part occlusion and unstable lighting.

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