Disambiguation in unknown object detection by integrating image and speech recognition confidences

Authors:
Yuko Ozasa;Yasuo Ariki;Mikio Nakano;Naoto Iwahashi
Affiliations:
Graduate School of System Informatics, Kobe University, Kobe, Hyogo, Japan;Graduate School of System Informatics, Kobe University, Kobe, Hyogo, Japan;Honda Research Institute Japan Co., Ltd., Wako-shi, Saitama, Japan;Keihanna Research Laboratories, National Institute of Information and Communications Technology, Soraku-gun, Kyoto, Japan
Venue:
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part I
Year:
2012

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Abstract

This paper presents a new method to detect unknown objects and their unknown names in object manipulation through man-robot dialog. In the method, the detection is carried out by using the information of object images and user's speech in an integrated way. Originality of the method is to use logistic regression for the discrimination between unknown and known objects. The accuracy of the unknown object detection was 97% in the case when there were about fifty known objects.