EIoU-distance loss: an automated team-wise player detection and tracking with jersey colour recognition in soccer

IF 3.2 4区计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Connection Science Pub Date : 2024-02-03 DOI:10.1080/09540091.2023.2291991

Banoth Thulasya Naik, Mohammad Farukh Hashmi, Aditya Gupta

引用次数: 0

Abstract

The surge in demand for advanced operations in sports video analysis has underscored the crucial role of multiple object tracking. This study addresses the escalating need for efficient and accurat...

查看原文本刊更多论文

EIoU-距离损失：利用球衣颜色识别自动检测和跟踪足球队中的球员

体育视频分析对高级操作的需求激增，这凸显了多目标跟踪的关键作用。本研究针对日益增长的对高效、准确的多目标跟踪的需求，提出了一种新的多目标跟踪技术。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Connection Science 工程技术-计算机：理论方法

CiteScore

6.50

自引率

39.60%

发文量

审稿时长

3 months

期刊介绍： Connection Science is an interdisciplinary journal dedicated to exploring the convergence of the analytic and synthetic sciences, including neuroscience, computational modelling, artificial intelligence, machine learning, deep learning, Database, Big Data, quantum computing, Blockchain, Zero-Knowledge, Internet of Things, Cybersecurity, and parallel and distributed computing. A strong focus is on the articles arising from connectionist, probabilistic, dynamical, or evolutionary approaches in aspects of Computer Science, applied applications, and systems-level computational subjects that seek to understand models in science and engineering.