Image search system

Abstract

We present a prototype system which enables users to explore the global structure for digital imagery archives as well as drill-down into individual pictures.Our search engine builds upon computer vision advances made over the past decade in low-level feature matching, large data handling and object recognition. We demonstrate hierarchical clustering among images semicooperatively shot around MIT, automatic linking of flickr photos and aerial frames from the Grand Canyon, and video segment identification for a TV broadcast. Moreover, our software tools incorporate visible vs infrared band selection, color content quantization and human face detection. Ongoing and future extensions of this image search system are discussed.