LifeConcept: An Interactive Approach for Multimodal Lifelog Retrieval through Concept Recommendation

Wei-Hong Ang, An-Zi Yen, Tai-Te Chu, Hen-Hsen Huang, Hsin-Hsi Chen
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引用次数: 10

Abstract

The major challenge in visual lifelog retrieval is the semantic gap between textual queries and visual concepts. This paper presents our work on the Lifelog Search Challenge 2021 (LSC'21), an annual comparative benchmarking activity for comparing approaches to interactive retrieval from multimodal lifelogs. We propose LifeConcept, an interactive lifelog search system that is aimed at accelerating the retrieval process and retrieving more precise results. In this work, we introduce several new features such as the number of people, location cluster, and object with color. Moreover, we obtain visual concepts from the images with computer vision models and propose a concept recommendation method to reduce the semantic gap. In this way, users can efficiently set up the related conditions for their requirements and search the desired images with appropriate query terms based on the suggestion.
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生命概念:一种基于概念推荐的多模态生命日志检索交互方法
视觉生活日志检索的主要挑战是文本查询和视觉概念之间的语义差距。本文介绍了我们在2021年生命日志搜索挑战(LSC'21)上的工作,这是一项年度比较基准活动,用于比较从多模式生命日志中进行交互检索的方法。我们提出了一个交互式生命日志搜索系统lifecconcept,旨在加速检索过程并检索更精确的结果。在这项工作中,我们引入了几个新的特征,如人数、位置集群和带颜色的对象。此外,我们利用计算机视觉模型从图像中获取视觉概念,并提出了一种概念推荐方法来减小语义差距。这样,用户可以有效地为自己的需求设置相关条件,并根据建议使用合适的查询条件搜索到想要的图像。
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Memento: A Prototype Lifelog Search Engine for LSC'21 XQC at the Lifelog Search Challenge 2021: Interactive Learning on a Mobile Device LifeSeeker 3.0: An Interactive Lifelog Search Engine for LSC'21 Enhanced SOMHunter for Known-item Search in Lifelog Data Flexible Interactive Retrieval SysTem 2.0 for Visual Lifelog Exploration at LSC 2021
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