Event-based home photo retrieval

Joo-Hwee Lim, P. Mulhem, Q. Tian
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引用次数: 1

Abstract

With rapid advances in sensor, storage, processor, and communication technologies, consumers can now afford to create, store, process, and share large digital photo collections. With more and more digital photos accumulated, consumers need effective and efficient tools to organize and access photos in a semantically meaningful way without too much manual annotation effort. From user studies, we confirm that users prefer to organize and access photos along semantic axes such as event, people, time, and place. In this paper, we propose a computational learning framework to construct event models from sample photos with event labels given by a user and to compute relevance measures of unlabeled photos to the event models. We demonstrate event-based retrieval on 2400 genuine home photos using our proposed approach.
基于事件的家庭照片检索
随着传感器、存储、处理器和通信技术的快速发展,消费者现在可以负担得起创建、存储、处理和共享大量数码照片。随着越来越多的数码照片的积累,消费者需要有效和高效的工具,以语义有意义的方式组织和访问照片,而不需要太多的手动注释工作。从用户研究中,我们确认用户更喜欢按照事件、人物、时间和地点等语义轴来组织和访问照片。在本文中,我们提出了一个计算学习框架,从带有用户给出的事件标签的样本照片中构建事件模型,并计算未标记照片与事件模型的相关性度量。我们使用我们提出的方法对2400张真实家庭照片进行了基于事件的检索。
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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