目标跟踪中基于IoU和中心点距离预测的尺度估计
Accurate Scale Estimation With IoU and Distance Between Centroids for Object Tracking
李绍明 1储珺 1冷璐 1涂序继1
作者信息
- 1. 南昌航空大学软件学院 南昌 330063;江西省图像处理与模式识别重点实验室 南昌 330063
- 折叠
摘要
通过分析基于交并比(Intersection over union,IoU)预测的尺度估计模型的梯度更新过程,发现其在训练和推理过程仅将IoU作为度量,缺乏对预测框和真实目标框中心点距离的约束,导致外观模型更新过程中模板受到污染,前景和背景分类时定位出现偏差.基于此发现,构建了一种结合IoU和中心点距离的新度量NDIoU(Normalization distance IoU),在此基础上提出一种新的尺度估计方法,并将其嵌入判别式跟踪框架.即在训练阶段以NDIoU为标签,设计了具有中心点距离约束的损失函数监督网络的学习,在线推理期间通过最大化NDIoU微调目标尺度,以帮助外观模型更新时获得更加准确的样本.在七个数据集上与相关主流方法进行对比,所提方法的综合性能优于所有对比算法.特别是在GOT-10k数据集上,所提方法的AO、SR0.50和SR0.75三个指标达到了 65.4％、78.7％和53.4％,分别超过基线模型4.3％、7.0％和4.2％.
Abstract
This paper first analyzes the gradient update process of the scale estimation model of intersection over union(IoU)prediction in detail,and finds that when the IoU is used as a metric in the training and inference pro-cess,the target scale estimation in the tracking process is inaccurate due to the absence of the constraint on the dis-tance between the two centroids.As a result,the template is polluted in the updating process of the object appear-ance model,which cannot discriminate the target and environment.With this insight,we propose a new metric NDIoU(normalization distance IoU)that combines the IoU and distance between two centroids to estimate the tar-get scale and proposes a new scale estimation method,which is embedded into the discriminative tracking frame-work.Using NDIoU as the label to supervise the distance between centroids,it is incorporated into the loss func-tion to facilitate the learning of the network.During online inference,NDIoU is maximized to fine-tune the target scale.Finally,the proposed method is embedded into the discriminative tracking framework and compared with re-lated state-of-the-art methods on seven data sets.The extensive experiments demonstrate that our method outper-forms all the state-of-the-art algorithms.Especially,on the GOT-10k dataset,our method achieves 65.4％,78.7％and 53.4％on the three metrics of AO,SR0.50 and SR0.75,which are better than the baseline by 4.3％,7.0％and 4.2％,respectively.
关键词
目标跟踪/交并比/尺度估计/中心点距离Key words
Object tracking/intersection over union(IoU)/scale estimation/distance between centroids引用本文复制引用
基金项目
国家自然科学基金(62162045)
江西省科技支撑计划项目(20192 BBE50073)
出版年
2024
国家科技期刊平台
NSTL
万方数据