We investigated a method for surviving tsunamis that involved the use of personal flotation devices (PFDs). In our work, we succeeded in numerically demonstrating that the heads of all the dummies wearing PFDs remained on the surface and were not dragged underwater after the artificial tsunami wave hit them. In contrast, the heads of all the dummies not wearing PFDs were drawn underwater immediately; these dummies were subsequently entrapped in a vortex. The results of our series of experiments are important as a first step to preventing the tragedies caused by tsunamis.

This paper deals with a problem of road tracking and vehicle positioning based on sequential images captured by a vehicle mounted monocular colour camera. The paper presents a new region‐based road tracking method, which is suitable for both structured and unstructured roads. The proposed method is based on our original road segmentation algorithm and estimates road model parameters from measurements obtained by analysis of segmented road region. Although the proposed method is tested over a limited range, evaluation on real image sequences shows promising results for various types of road

Road region is an important information for guidance of autonomous vehicles or robots. The goal of this research is to develop robust monocular algorithm suitable for region based road detection. This paper deals with a problem, how to estimate probability density function (pdf) of road region appearing in sequential images. The key idea is to construct pdf from temporal sequence of observations throughout the image sequence, where pdf has color components and spatial coordinates as its variables. The problem of pdf estimation was formulated in terms of Bayesian filtering, and sequential Monte-Carlo method was addopted as a tool to solve the problem. The proposed method was evaluated on real image sequences, and effectiveness of the proposed method is demonstrated.

This paper presents a novel method for monocular vision based pathway estimation. In this context, the pathway means a trajectory which an autonomous vehicle should follow to avoid departure from the road. The proposed method is based on our previous work on road region segmentation, and exploits the road region extracted from monocular sequential images to estimate parameters of the pathway model. Since the proposed method doesn't require road surface marking, it is suitable for unstructured roads, while it still works for structured roads too. The proposed method is tested on real image sequences and compared with edge based techniques.

SUMMARYIn various fields such as movement detection, stereo matching, image morphing, image synthesis, and image recognition, automatic determination of the image correspondence is a very basic problem. In this paper, the relation establishing correspondence between a prototype and the images (i.e., warping function) is treated and the method of determination of such function is proposed. The proposed method is based on the variational principle. The warping function is determined as the solution which minimizes the brightness differences between the pixels under smoothness constraints. Examples on applications of the proposed procedure of determination of warping functions are presented which indicate the effectiveness of the method.