Yasuhiro Oue

A flexible 3D modeling system based on combining shape-from-silhouette with light-sectioning algorithm

In this paper we present a flexible modeling system for obtaining the texture-mapped 3D geometric model. The modeling system uses an algorithm combining shape-from-silhouette with light-sectioning. In the algorithm, at first, a rough shape model is obtained by shape-from-silhouette method almost automatically. Next, concavities and complex parts on the object surface are obtained by light-sectioning method with manual scanning. For applying light-sectioning method to volume data, we propose volumetric light-sectioning algorithm. Then our modeling system can realize easy and accurate generation of 3D geometric model.

Improved 3D head reconstruction system based on combining shape-from-silhouette with two-stage stereo algorithm

In this paper, we present a quality improvement algorithm for the system, which models a human head. We have already proposed and applied the hybrid algorithm combining shape-from-silhouette with active stereo to our product of 3D head reconstruction system. Our system is characterized by the ability of the reconstruction of the whole shape and texture of the human head, even the black hair parts, while other existing systems cannot do it. Feature-based stereo algorithm adopted into our current system is the fast and robust approach. However, the depth data may be sparse and the accuracy depends on how accurate the edge detection is. On the other hand, area-based stereo algorithms generally provide dense depth data and can apply subpixel estimation, but it is comparatively time-consuming and may be inaccurate influenced by the difference of how to reflect the object in each image. To overcome these problems for improving our system practicably, we propose a novel two-stage stereo algorithm. In our algorithm, first, we adopt feature-based approach to get the depth data robustly. Next, an interpolation of the depth data is performed to predict the depth data at the unestimated pixels on the edge. Finally, applying area-based approach and subpixel estimation refine the depth data. In this paper, we describe our hybrid modeling algorithm and two-stage stereo algorithm with some experimental results.

Handheld camera 3D modeling system using multiple reference panels

A novel 3D modeling system in which a target object is easily captured and modeled by using a hand-held camera with several reference panels is presented in this paper. The reference panels are designed to be able to obtain the camera position and discriminate between each other. A conventional 3D modeling system using a reference panel has several restrictions regarding the target object, specifically the size and its location. Our system uses multiple reference panels, which are set around the target object to remove these restrictions. The main features of this system are as follows: 1) The whole shape and photo-realistic textures of the target object can be digitized based on several still images or a movie captured by using a hand-held camera; as well as each location of the camera that can be calculated using the reference panels. 2) Our system can be provided as a software product only. That means there are no special requirements for hardware; even the reference panels , because they can be printed from image files or software. 3) This system can be applied to digitize a larger object. In the experiments, we developed and used an interactive region selection tool to detect the silhouette on each image instead of using the chroma -keying method. We have tested our system with a toy object. The calculation time is about 10 minutes (except for the capturing the images and extracting the silhouette by using our tool) on a personal computer with a Pentium-III processor (600MHz) and 320MB memory. However, it depends on how complex the images are and how many images you use. Our future plan is to evaluate the system with various kind of objects, specifically, large ones in outdoor environments.

Dynamic access load balancing on the parallel secondary storage

A massively parallel computer handles a massive amount of data with simultaneous access requests from multiple processors, and therefore it must have a large-capacity secondary storage system of very high concurrency. Such a storage system should consist of many disks that are connected in parallel. With such large-scale parallel disk systems, access load balancing is extremely important in order to enhance the effective operation of all disks. In this paper, we propose a parallel file access method named DECODE (Dynamic Express Changing Of Data Entry) which performs dynamic load balancing over all disks according to the load status of each disk. DECODE can achieve load balancing by changing the disk used for writing data to a low-load disk. The efficiency of this method is verified by preliminary performance evaluation using software simulation under various access conditions, by changing the access pattern and the access size. The effect of some of the parameters used in the method is also evaluated.