利用情境資訊的影像搜尋

Abstract

With the prevalence of capture devices, people are used to share their images and videos on the social media (e.g., Flickr and Facebook). To provide relevant information (e.g., reviews, landmark names, products) for these uploaded media, the need for effective and efficient visual search (e.g., image retrieval, mobile visual search, product search) is emerging. It enables plenty of applications such as recommendation, annotation, and advertisement. The state-of-the-art approaches (visual features) usually suffer from low recall rates because small changes in lighting conditions, viewpoints, or occlusions could degrade the performance significantly. We observe that enormous media collections are along with rich contextual cues such as tags, geo-locations, descriptions, and time. Hence, we propose to exploit different contextual information with the state-of-the-art visual features for solving the above challenges, and are able to improve the retrieval accuracy and provide diverse search results.