多模态深层次高置信度融合跟踪算法  

Multi-modal Deep-level High-confidence Fusion Tracking Algorithm

作　　者：高伟 薛杉 胡秋霞 李嘉琦 田杰 饶晔 杨举 GAO Wei;XUE Shan;HU Qiu-Xia;LI Jia-Qi;TIAN Jie;RAO Ye;YANG Ju(School of Computer Science,Xi’an Aeronautical University,Xi’an 710077,China;Research and Development Center of Xi’an,the 15th Research Institute of China Electronics Technology Group,Xi’an 710005,China)

机构地区：[1]西安航空学院计算机学院,西安710077 [2]中国电子科技集团第十五研究所西安研发中心,西安710005

出　　处：《计算机系统应用》2024年第9期153-163,共11页Computer Systems & Applications

基　　金：陕西省自然科学基金面上项目(2023JCYB194,2024JCYBMS169);西安航空学院校级科研基金(2023KY1205)。

摘　　要：为解决单目标跟踪中因目标外观及环境变化导致的跟踪失败问题,提出一种多模态深层次高置信度融合跟踪算法.首先构建目标颜色模型和基于双线性插值HOG特征形状模型的高维度多模态模型,之后对候选目标利用粒子滤波进行搜索.针对模型融合的难点,通过准确量化形状和颜色模型多种置信度并设计高置信度融合准则,以实现该多模态模型中不同置信度的深层次自适应加权平衡融合.最后针对模型更新参数固定的问题,设计非线性分级平衡更新策略.经过在OTB-2015数据集上的测试,发现该算法的平均CLE和OS在所有参照算法表现中均表现最佳,其值分别为30.57和0.609.此外,其FPS为15.67,满足了跟踪算法在一般情况下的实时性要求.在某些常见的特定场景中,其精确率、成功率指标在多数情况下的表现也超过了同类顶尖算法.This study proposes a multi-modal deep-level high-confidence fusion tracking algorithm in response to the tracking failure issues caused by changes in target appearance and environment in single-target tracking applications.First,a high-dimensional multi-modal model is constructed utilizing the target’s color model combined with a shape model based on bilinear interpolation HOG features.Then,candidate targets are searched using particle filtering.The challenge posed by model fusion is addressed by scrupulously quantifying a range of confidences in shape and color models.This is followed by the introduction of a high-confidence fusion criterion,which enables a deeply-adaptive,weighted,and balanced fusion with different confidence levels in the multi-modal model.To counter the issue of static model update parameters,a nonlinear,graded balanced update strategy is designed.Upon testing on the OTB-2015 dataset,this algorithm’s average CLE and OS metrics demonstrated superior performance compared to all reference algorithms,with values of 30.57 and 0.609,respectively.Moreover,with an FPS of 15.67,the algorithm fulfills the realtime operation requirements inherent in tracking algorithms under most conditions.Notably,in some common specific scenarios,the accuracy and success rate of the algorithm also outperform the top-tier algorithms in most cases.

关 键 词：视觉目标跟踪 多模态 置信度融合 深层次加权 分级平衡更新 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]