Object Categorization Using Multimodal Information

Abstract

In this paper unsupervised categorization by robots is explored. We propose an unsupervised multimodal categorization based on audio-visual and haptic information. The robot uses its physical embodiment to grasp and observe an object from various view points as well as listen to the sound during the observation. The proposed categorization method is an extension of probabilistic latent semantic analysis (pLSA), which is a statistical technique. At the same time the proposed method provides a probabilistic framework for inferring the object property from limited observations. The validity of the proposed method is shown through some experimental results