A Probabilistic Framework for Multimodal Retrieval using Integrative Indian Buffet Process
Bahadır Özdemir, Larry Steven Davis · 2014
We propose a multimodal retrieval procedure based on latent feature models. The procedure consists of a Bayesian nonparametric framework for learning under-lying semantically meaningful abstract features in a multimodal dataset, a proba-bilistic retrieval model that allows cross-modal queries and an extension model for relevance feedback. Experiments on two multimodal datasets, PASCAL-Sentence and SUN-Attribute, demonstrate the effectiveness of the proposed retrieval proce-dure in comparison to the state-of-the-art algorithms for learning binary codes. 1