A Two-Level Lifelog Search Engine at the LSC 2019

Isadora Nguyen Van Khan, Pranita Shrestha, Min Zhang, Yiqun Liu, Shaoping Ma
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引用次数: 7

Abstract

The rise of affordable wearable devices makes visual lifelog data easier to collect. This data can then be retrieved as an aside memory usable as well for people with memory issues or in daily life to be more efficient. This paper presents the retrieval system designed for the Lifelog Search Challenge 2019 competition. This retrieval system offers two search levels: a semantic one and an image-based one. The data used for the indexing for both levels (semantic data for the text-based method or combinations of HSV Histogram and BRIEF features for the example-based one) as well as the architecture of the overall system is described. Results from our experiments are promising. The text-based search engine has disparate results that strongly depend on the keywords used for the query. For the example search engine, the best features are composed of both HSV histogram and BRIEF features. Despite encouraging results, the processing time appears to be a limitation.
LSC 2019上的两级生活日志搜索引擎
价格实惠的可穿戴设备的兴起使得视觉生活日志数据更容易收集。这些数据可以作为备用记忆检索,也可以用于有记忆问题的人或在日常生活中提高效率。本文介绍了为2019年Lifelog搜索挑战赛设计的检索系统。该检索系统提供了两个搜索级别:语义搜索级别和基于图像的搜索级别。描述了用于两个级别的索引的数据(基于文本的方法的语义数据或基于示例的方法的HSV直方图和BRIEF特征的组合)以及整个系统的体系结构。我们的实验结果很有希望。基于文本的搜索引擎具有完全不同的结果,这些结果强烈依赖于用于查询的关键字。对于示例搜索引擎,最佳特征由HSV直方图和BRIEF特征组成。尽管结果令人鼓舞,但处理时间似乎是有限的。
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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