lifeXplore at the Lifelog Search Challenge 2023

Klaus Schoeffmann
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引用次数: 1

Abstract

Searching substantial data archives of lifeloggers is a challenging task. The Lifelog Search Challenge (LSC) is an annually held competition with the aim of encouraging international teams to develop interactive content retrieval systems capable of searching large lifelog databases. LSC takes place as a live event co-located with the ACM International Conference on Multimedia Retrieval (ICMR), where teams compete against each other by solving retrieval tasks issued by the lifelogger. This paper presents our newest version of lifeXplore, a lifelog retrieval system that has been participating in LSC since 2018. For this year, we significantly redesign the entire system (backend, middleware, and frontend) and integrate free text-search using embeddings from vision transformers trained with large sets of text-image pairs. We present a novel architecture for multi-source search, where results from image embeddings are used together with results from traditional content analysis (for objects, concepts, and recognized text). We also perform intensive analysis of vision transformer models in order to know which one fits best to the requirements of the LSC.
lifeexplore在2023年生命日志搜索挑战赛上
搜寻大量的生命记录者数据档案是一项具有挑战性的任务。生命日志搜索挑战赛(LSC)是一项每年举办的竞赛,旨在鼓励国际团队开发能够搜索大型生命日志数据库的交互式内容检索系统。LSC是与ACM多媒体检索国际会议(ICMR)同时举办的现场活动,团队通过解决由生命记录员发出的检索任务相互竞争。本文介绍了我们最新版本的lifeXplore,这是一个自2018年以来一直参与LSC的生活日志检索系统。今年,我们对整个系统(后端、中间件和前端)进行了重大的重新设计,并使用由大量文本图像对训练的视觉转换器嵌入来集成免费的文本搜索。我们提出了一种新的多源搜索架构,其中图像嵌入的结果与传统内容分析(对象、概念和可识别文本)的结果一起使用。我们还对视觉变压器模型进行了深入的分析,以了解哪一个最适合LSC的要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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