Category search is a searching activity where the user has an example images and searches for other images of the same category.
This activity often requires appropriate keywords of target categories making it difficult to search images without prior knowledge of appropriate keywords.
Text annotations attached to images are a valuable resource for helping users to find appropriate keywords for the target categories.
We propose an image exploration system in this paper for category image search without the prior knowledge of category keywords.
Our system integrates content-based and keyword-based image exploration and seamlessly switches exploration types according to user interests.
The system enables users to learn target categories both in image and keyword representation through exploration activities.
Our user study demonstrated the effectiveness of image exploration using our system, especially for the search of images with unfamiliar category compared to the single-modality image search.
Kazuyo Mizuno, Daisuke Sakamoto, and Takeo Igarashi. AssisTag: Seamless integration of Content-based and Keyword-based Image Exploration for Category Search. Journal of Imaging Science & Technology, 60(6):60401–1–60401–12, 2016.
Kazuyo Mizuno, Daisuke Sakamoto, and Takeo Igarashi. AssisTag: Seamless integration of Content-based and Keyword-based Image Exploration for Category Search. In Proceedings of IS&T/SPIE Conference on Visualization and Data Analysis (VDA ’17)(Journal Track), pages 58–69, 2017.