2003/04/05 by Ka-Ping Yee, Kirsten Swearingen, Kevin Li +1 · 5 citations
Computer Science · #Advanced Image and Video Retrieval Techniques #Image Retrieval and Classification Techniques #Video Analysis and Summarization
paper · doi:10.1145/642611.642681
openalex publication_date 2003/04/05 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29
There are currently two dominant interface types for searching and browsing large image collections: keyword-based search, and searching by overall similarity to sample images. We present an alternative based on enabling users to navigate along conceptual dimensions that describe the images. The interface makes use of hierarchical faceted metadata and dynamically generated query previews. A usability study, in which 32 art history students explored a collection of 35,000 fine arts images, compares this approach to a standard image search interface. Despite the unfamiliarity and power of the interface (attributes that often lead to rejection of new search interfaces), the study results show that 90% of the participants preferred the metadata approach overall, 97% said that it helped them learn more about the collection, 75% found it more flexible, and 72% found it easier to use than a standard baseline system. These results indicate that a category-based approach is a successful way to provide access to image collections.