Intuitive interfaces have become increasingly important multimedia applications, from personal photo collection to professional management systems. This research brings a novel intuitive interactive interface for browsing of large image and video collections that visualizes underlying structure of the dataset by its size and spatial relations. In order to achieve this, images/frames are initially clustered using an unsupervised graph-based clustering algorithm. By selecting images in a hierarchical layout of the screen, user can intuitively navigate through the collection. The experimental results demonstrate a significant speed-up in a content search scenario compared to a standard browsing interface, as well as inherent intuitiveness of the system.
Our user evaluation of FreeEye browsing interface was published online as a pre-print, and can be found at:
Interactive search and browsing interface for large-scale visual repositories.
Kan Ren, Risto Sarvas, Janko Calic.
Due to the rapid proliferation of both user-generated and broadcasted content, the interfaces for search and browsing of visual media have become increasingly important. This paper presents a novel intuitive interactive interface for browsing of large-scale image and video collections. It visualises underlying structure of the dataset by the size and spatial relations of displayed images. In order to achieve this, images or video key-frames are initially clustered using an unsupervised graph-based clustering algorithm. By selecting images that are hierarchically laid out on the screen, user can intuitively navigate through the collection or search for specific content. The extensive experimental results based on user evaluation of photo search, browsing and selection as well as interactive video search demonstrate good usability of the presented system and improvement when compared to the standard methods for interaction with large-scale image and video collections.