面向多目标跟踪的关联相似度神经网络学习（英文）

来源 :Frontiers of Information Technology & Electronic Engineering | 被引量 : 0次 | 上传用户：qcolin

【摘要】

：

为解决视频多目标跟踪问题,提出一种特征和度量联合学习的深度神经网络架构,称为关联相似度网络。关联相似度网络以端到端的方式学习跟踪轨迹和检测结果之间的关联相似度。针对有缺陷的检测结果,关联相似度网络同时学习矩形框回归、目标分类和相似度回归3个任务。不同于现有基于对比排序思想的方法,我们直接训练一个二分类器来学习跟踪轨迹与检测结果的关联相似度,同时设计了损失函数来约束匹配集合元素的个数。得益于上述设计

【作者】

：

马良钟巧勇张营营谢迪浦世亮

【出处】

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Frontiers of Information Technology & Electronic Engineering

【发表日期】

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2021年09期

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