Three-Way Aspect Model (TWAPM) and Co-training for Image Retrieval

摘要

The goal of this work is to investigate the applicability of two probabilistic approaches, namely Three-Way Aspect Model (TWAPM) and Co-training, to retrieve images represented by multiple feature types from large image collections. We test these approaches in a learning context via relevance feedback from user. Our experiments show that Co-training may be a better choice than TWAPM for a Web-based Image Retrieval System.