An Interactive Image Retrieval Approach to Searching for Images on Social Media

Manali Gaikwad, O. Hoeber
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引用次数: 5

Abstract

Searching for images posted within social media services such as Twitter relies on matching textual queries to the contents of the posts that include the images. Unfortunately, social media posts may not always provide accurate or meaningful descriptions of the contents of the embedded images, making searching for images a challenging task. In this research, we augment the textual contents of the posts with new information extracted from the images using image processing and deep learning methods, and provide a visual interface to enable interactive image retrieval. A user study was conducted with 28 participants to collect evidence on how our approach was used in relation to Vakkari's three-stage model of information seeking. We also analyzed participants' perceptions of usefulness, ease of use, and satisfaction in comparison to a common grid-based image search interface. The results from this study highlight the value of providing visual and interactive features to enable searchers to discover images from social media sources.
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一种交互式图像检索方法在社交媒体上搜索图像
搜索在Twitter等社交媒体服务中发布的图像依赖于将文本查询与包含图像的帖子内容相匹配。不幸的是,社交媒体帖子可能并不总是对嵌入图像的内容提供准确或有意义的描述,这使得搜索图像成为一项具有挑战性的任务。在本研究中,我们使用图像处理和深度学习方法从图像中提取新的信息来增强帖子的文本内容,并提供一个可视化界面来实现交互式图像检索。我们对28名参与者进行了一项用户研究,以收集证据,证明我们的方法是如何与Vakkari的三阶段信息寻找模型相关联的。我们还分析了与普通的基于网格的图像搜索界面相比,参与者对有用性、易用性和满意度的看法。这项研究的结果强调了提供视觉和互动功能的价值,使搜索者能够从社交媒体资源中发现图像。
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