In this paper, we propose robust sensing method against bubble noises in aquatic environments with a stereo vision system. Usually, three-dimensional (3-D) measurement by robot vision techniques is executed under the assumptions that cameras and objects are in aerial environments. However, an image distortion occurs when vision sensors measure objects in liquid. It is caused by the refraction of the light on the boundary between the air and the liquid, and the distorted image brings errors in a triangulation for the range measurement. Additionally, it is often the case that there exist air bubbles in the field of view when we observe aquatic environments. Therefore, it becomes difficult to acquire clear images because of these view-disturbing noises. As to the former problem, accurate 3-D coordinates of objects' surfaces in liquid are measured by taking for calculating the refraction effect. As to the latter problem, bubble noises are eliminated from a moving image to divide objects in the image into still backgrounds, moving objects, and bubble noise by an image processing technique. Experimental results showed the effectiveness of our proposed method

This paper presents a unification-based approach to Japanese honorifics based on a version of HPSG (Head-driven Phrase Structure Grammar). Utterance parsing is based on lexical specifications of each lexical item, including honorifics, and a few general PSG rules using a parser capable of unifying cyclic feature structures. It is shown that the possible word orders of Japanese honorific predicate constituents can be automatically deduced in the proposed framework without independently specifying them. Discourse Information Change Rules (DICRs) that allow resolving a class of anaphors in honorific contexts are also formulated.