计算机科学
跟踪(教育)
鉴定(生物学)
对象(语法)
视频跟踪
协议(科学)
集合(抽象数据类型)
度量(数据仓库)
人工智能
数据挖掘
机器学习
计算机视觉
生物
心理学
替代医学
教育学
医学
植物
程序设计语言
病理
作者
Kevin Smith,Daniel Gática-Pérez,Jean‐Marc Odobez,Silèye Ba
标识
DOI:10.1109/cvpr.2005.453
摘要
Multiple object tracking (MOT) is an active and challenging research topic. Many different approaches to the MOT problem exist, yet there is little agreement amongst the community on how to evaluate or compare these methods, and the amount of literature addressing this problem is limited. The goal of this paper is to address this issue by providing a comprehensive approach to the empirical evaluation of tracking performance. To that end, we explore the tracking characteristics important to measure in a real-life application, focusing on configuration (the number and location of objects in a scene) and identification (the consistent labeling of objects over time), and define a set of measures and a protocol to objectively evaluate these characteristics.
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