From Pixels to Semantic Spaces: Advances in Content-Based Image Retrieval

Abstract

The paradigm for image retrieval has evolved from low-level image representations to semantic concept models to higher-level semantic inferences. UCSD's Statistical Visual Computing Laboratory has developed effective techniques for each paradigm that equate retrieval with classification and strive for minimum-probability-of-error optimality.