Ly-Duyen Tran, Binh T. Nguyen, Liting Zhou, C. Gurrin
{"title":"MyEachtra: Event-Based Interactive Lifelog Retrieval System for LSC’23","authors":"Ly-Duyen Tran, Binh T. Nguyen, Liting Zhou, C. Gurrin","doi":"10.1145/3592573.3593100","DOIUrl":null,"url":null,"abstract":"Retrieval is a fundamental challenge within the research community of lifelog and the Lifelog Search Challenge (LSC) has been an important annual benchmarking activity for interactive lifelog retrieval systems since 2018. This paper proposes MyEachtra (/mai-AK-truh/), a system designed for the upcoming LSC’23 workshop. Improved upon MyScéal, which was the top performing system from LSC’20 to LSC’22, MyEachtra includes modifications to address the challenges of non-owner user understanding of lifelog contexts and open-ended lifelog question answering. Specifically, MyEachtra shifts the focus from images to events as retrieval units. Events are segmented using location metadata as well as visual and time differences between successive images. A pilot study on different approaches to aggregate images into events was conducted to test the automatic performance of the system, which showed promising results. For known-item queries, showing only the top 3 events proved to be adequate to find relevant images. However, future evaluation of the performance for ad-hoc and question-answering queries is necessary for a complete analysis of the MyEachtra.","PeriodicalId":147486,"journal":{"name":"Proceedings of the 6th Annual ACM Lifelog Search Challenge","volume":"87 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 6th Annual ACM Lifelog Search Challenge","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3592573.3593100","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Retrieval is a fundamental challenge within the research community of lifelog and the Lifelog Search Challenge (LSC) has been an important annual benchmarking activity for interactive lifelog retrieval systems since 2018. This paper proposes MyEachtra (/mai-AK-truh/), a system designed for the upcoming LSC’23 workshop. Improved upon MyScéal, which was the top performing system from LSC’20 to LSC’22, MyEachtra includes modifications to address the challenges of non-owner user understanding of lifelog contexts and open-ended lifelog question answering. Specifically, MyEachtra shifts the focus from images to events as retrieval units. Events are segmented using location metadata as well as visual and time differences between successive images. A pilot study on different approaches to aggregate images into events was conducted to test the automatic performance of the system, which showed promising results. For known-item queries, showing only the top 3 events proved to be adequate to find relevant images. However, future evaluation of the performance for ad-hoc and question-answering queries is necessary for a complete analysis of the MyEachtra.