Joint dictionary learning and topic modeling for image clustering

A new Bayesian model is proposed, integrating dictionary learning and topic modeling into a unified framework. The model is applied to cluster multiple images, and a subset of the images may be annotated. Example results are presented on the MNIST digit data and on the Microsoft MSRC multi-scene image data. These results reveal the working mechanisms of the model and demonstrate state-of-theart performance.

• Type: Journal
• Year: 2011
• Where: ICASSP
• Authors: Lingbo Li, Mingyuan Zhou, Eric Wang, Lawrence Carin
• Keywords: ICASSP 2011, Image, MNIST Digit Data, MSRC Multi-scene Image, Signal Processing