We have developed a multi-projector display environment called the projector array system. Tiled images are projected onto a large screen from the multiple projectors, and these images are connected seamlessly by an image transforming mechanism. This mechanism is executed in real-time by a special hardware called the PA board that modifies geometrical errors caused from each projector. In this paper, we apply this environment to a live image display system. In order to capture wide view-angle and high resolution images, we use a multi-camera system that has the same alignment as the multi-projector system. When we configure the total system, a method for modifying geometrical errors caused by the camera system, and another method for modifying errors caused from a parameter mismatch between the camera and the projector are required. In this system, therefore, we implement these methods so that three errors caused from: (1) projection environment; (2) camera system; and (3) parameter's mismatch are modified altogether by the PA board at the same time. A prototype experiment enables a naturalistic image display.

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Abstract This paper describes a practical method that enables actual images to be converted so that they can be projected onto an immersive projection display (IPD) screen. IPD screens are particularly unique in that their angle of view is extremely wide; therefore, the images projected onto them need to be taken on a special format. In practice, however, it is generally very difficult to shoot images that completely satisfy the specifications of the targeting IPD environment due to cost, technical problems or other reasons. To overcome these problems, we developed a method to modify the images by abandoning geometrical consistency. We were able to utilize this method by assuming that the given image was shot according to a special projection model. Because this model differed from the actual projection model with which the image was taken, we termed it the pseudo‐projection model. Since our method uses simple geometry, and can easily be expressed by a parametric function, the degree of modification or the time sequence for modification can readily be adjusted according to the features of each type of content. Copyright © 2003 John Wiley & Sons, Ltd.

We have developed an immersive projection system which enables the viewer to experience a truly immersive feeling by looking at a wide-angle image on multiple surrounding screens. Our system is similar to previous systems but has a unique point in that it includes a new motion-based ride system as part of the environment. This ride system includes a seat that can be moved and rotated to give a rider (viewer) a sense of acceleration. We have used this environment to develop an application in which the viewer can experience a sensation of moving around in a virtual world while riding a virtually moving machine, such as a virtual vehicle.

We present a closed-form solution for the rotation-estimation problem, by introducing the same algorithm used for solving the perspective three-point problem. The rotation-estimation problem is defined as estimating the relative rotation of two camera images when the translation is known. The perspective three-point problem, in which the pose of a single camera is estimated from the location of three points, is a classical problem in the field of computer vision, and a closed-form solution for it has already been established. The two problems are not obviously similar, but we show by making some parameter exchanges that they are essentially equivalent. Actual applications using the rotation-estimation problem are also explained.

A new approach is described for estimating the sensor configuration of a mobile robot, given a set of range data in a known environment. A robot is equipped with multiple sensors. The environment is represented by a set of line segments in any plane. The perceptual equivalence classes of the sensor configuration space (x, y, /spl theta/) are pre-computed. Two sensor configurations are considered equivalent if the mapping from the sensors to the visible line segments is identical. When a set of range data is observed at an execution time, a searching process is invoked in energy equivalence class. Since the mapping of the sensors to obstacles is constant in a class, the objective function for maximum likelihood estimation behaves well. An efficient algorithm to search for the minima is presented. A simulation using randomly generated sensor data in randomly created robot environments is shown.

We introduce a new environment to make and play interactive contents with more than video game quality. The system consists of a projector array, a viewer and an editor for the special contents. The projector array projects multiple digital images seamlessly both in time and space, thus a very high quality video projection system. The viewer features a function to composite a passive video and interactive CG in real time. The editor is a high-end non-linear editing system combined with some new plug-in software to pre-compute the information necessary for real-time compositing. A new method of digital image recognition assisted by human operators is used. Unlike general purpose computer vision algorithms, it minimizes the error of 3D estimation at the compositing position. We call this approach V2R or the video-based virtual reality. It allows the operator to experience interactive communications with objects in a very high quality video.

We propose a method to estimate camera parameters from video sequences for the purpose of natural CG composite remarking the problem of stabilization. When the video is taken under wrong condition, it is inescapable that the estimated parameters contain nonnegligible errors which cause an unexpected shaking of CG object. To avoid this problem, we introduce a smoothing technique taking account of a property of synthesizing object. The method is based on an idea that the estimated camera parameters need not to be correct so far as composite is natural, and can be varied according to the condition of CG object even though the given images are same. Introducing the factor of locational and temporal smoothness to estimate the camera parameters, we can accomplish an appropriate stabilization for particular CG composite.

Failures in mobile robot navigation are often caused by errors in localizing the robot relative to its environment. This paper explores the idea that these errors can be considerably reduced by planning paths taking the robot through positions where pertinent features of the environment can be sensed. It introduces the notion of a "sensory uncertainty field" (SUF). For every possible robot configuration q, this field estimates the distribution of possible errors in the robot configuration that would be computed by a localization function matching the data given by the sensors against an environment model, if the robot was at q. A planner is proposed which uses a precomputed SUF to generate paths that minimize expected errors or any other criterion combining, say, path length and errors. This paper describes in detail the computation of a specific SUF for a mobile robot equipped with a classical line-striping camera/laser range sensor. It presents an implemented SUF-based motion planner for this robot and shows paths generated by this planner. Navigation experiments were conducted with mobile robots using paths generated by the SUF-based planner and other paths. The former paths were tracked with greater precision than the others. The final section of the paper discusses additional research issues related to SUF-based planning.>

The authors introduce an approach to motion planning with uncertainty for mobile robots. Given a model of the robot's environment, a sensory uncertainty field (SUF) is computed over the robot's configuration space. At every configuration q, the SUF is an estimate of the uncertainty in the sensed configuration that would be computed by matching the data given by the robot sensors against the environment model, if the robot was at the configuration q. A planner then makes use of the computed SUF to generate paths that minimize the expected errors. The computation of a SUF is described for a classical line-striping camera/laser range sensor. An implemented SUF-based motion planner for a robot equipped with this sensor is presented.>