We developed a novel multipoint measurement system capable of acquiring video and sound at more than 100 points in a "synchronized" manner. In this paper, we first describe the specification of the system and how the system works in detail. Then we report some experimental results that confirm the performance of the system. We also describe test data set we provided for MPEG (moving picture experts group) multi-viewpoint video coding activities. Using this system, we are planning to conduct projects to measure humans and their activities, collect a large volume of real-world data of video and sound, and release them to the public

This paper reports a method for estimating human spine posture using the front and side views of a human body taken by a video camera. We present here a new 3D model to estimate the spine posture using connected vertebra spheres. In this model, each vertebra forming the spine is approximated as a sphere. The spine is approximated as a series of spheres connecting each other. Each sphere has the control points to represent the outer shape of the body. The spine posture is estimated by moving the sphere and the control points. The estimation is performed by calculating the matching ratio between a projected image of the model and an input image. X-ray CT slices are used for the construction of the model. We applied the proposed method to real human images. The experimental results show that our 3D model worked reasonably well for the estimation of human spine posture based on real human images.

This paper presents an expanded system for the online recognition of handwritten mathematical formulas. Our target handwritten mathematical formulas are strokes drawn on a data tablet. This system recognizes such strokes as components of mathematical formulas on the basis of their positions and combinations. Including matrix structures, general mathematical expressions are acceptable for this system. Each recognition result is acquired as a L/sup A/T/sub E/X source code. This system also has a preview function to enable a more highly intuitive recognition result. In recognition experiments, this system proved to be fairly feasible in handling handwritten mathematical formulas in real-time.

This paper presents a new system for the online and real-time recognition of handwritten mathematical formulas. Mathematical formulas are inputted into the system as hand drawings on a computer screen using a data tablet. The system analyzes the inputted data stroke by stroke in order to recognize the structure of the formula based on the relationship of bonding boxes that include components of the formula. A recognized result is obtained as a source code from the "LATEX" type serving system. Our system can recognize arbitrary combinations of superscripts, subscripts, square roots, overlines, underlines, and fractions. The input of the mathematical formula is independent of stroke order. In several experiments, the system proved to be very effective for inputting various mathematical formulas in real-time.

This paper introduces a method that can generate continuous human walking motion automatically on an arbitrary path in a three-dimensional (3D) modelled scene. The method is based on a physical approach that solves the boundary value problem. In the motion generation stage, natural-looking walking motion, which includes plane walking, walking upstairs and downstairs and walking on a curved path, is created by applying dynamics and kinematics. The human body is approximated as a simple rigid skeleton model, and dynamic motion is created based on the ground reaction force of the human foot. To adapt to the 3D environment, the 3D walking path is divided into steps which are tagged with the parameters needed for motion generation, and step-by-step motion is connected end-to-end. Additional features include fast calculation and a reduced need for user control. The proposed method can produce interesting human motion and can create realistic computer animation scenes. Copyright © 2000 John Wiley & Sons, Ltd.

This paper describes a method for the automated anatomical labeling of the bronchial branch extracted from a three-dimensional (3-D) chest X-ray CT image and its application to a virtual bronchoscopy system (VBS). Automated anatomical labeling is necessary for implementing an advanced computer-aided diagnosis system of 3-D medical images. This method performs the anatomical labeling of the bronchial branch using the knowledge base of the bronchial branch name. The knowledge base holds information on the bronchial branch as a set of rules for its anatomical labeling. A bronchus region is automatically extracted from a given 3-D CT image. A tree structure representing the essential structure of the extracted bronchus is recognized from the bronchus region. Anatomical labeling is performed by comparing this tree structure of the bronchus with the knowledge base. As an application, we implemented the function to automatically present the anatomical names of the branches that are shown in the currently rendered image in real time on the VBS. The result showed that the method could segment about 57% of the branches from CT images and extracted a tree structure of about 91% in branches in the segmented bronchus. The anatomical labeling method could assign the correct branch name to about 93% of the branches in the extracted tree structure. Anatomical names were appropriately displayed in the endoscopic view.

This paper surveys 3D measurement technologies for computer animation and considers unsolved problems on this subject. 3D measurement technologies are actually very important for converting various 3D objects in the real world to 3D models in the virtual world for computer animation. Current 3D measurement technologies have been developed mainly for measuring objects in industrial or scientific fields, such as factory automation or remote sensing. Consequently most 3D measurement systems are not necessarily suitable to measure various objects including human bodies directly. Medical equipment like X-ray CT and MRI are not handy tools. It is interesting to reconsider the remaining problems today for better 3D measurement in the future. This paper first surveys the current 3D measurement technologies ranging from the most basic feature based method to various types of rangefinders, then considers the remaining problems for ideal 3D measurement technologies for computer animation.

Proposes a scheme that offers accurate and robust identification of human faces. The scheme is characterized by four aspects: facial feature detection using color image segmentation; target image extraction using a sub-space classification method; robust feature extraction based on K-L expansion of an invariant feature space; and face classifier training based on 3D CG modeling of the human face. The scheme's flexibility under a wide range of image acquisition conditions has been confirmed through the assessment of an experimental face identification system.>

Proposes a variable filter, a new high-resolution Hough transform method. A voted value at the point ( rho , theta ) on the Hough space is transformed into a value distribution by the variable filter, and voting is performed according to the distribution. The shape and size of the variable filter changes dynamically with the quantization size and the line parameters ( rho , theta ). Statistical experiments show that the filter can improve extraction performance and reduce the mean error of extracted line parameters even with noisy images.>

This paper presents a new ray-tracing acceleration technique called Pixel Selected Ray-Tracing (PSRT). PSRT uses undersampling based on Iterative Central Point Selection(ICPS) along with checking for similarities among trees in neighboring pixels. By using ICPS and trees, the largest danger of missing object borders can be drastically reduced. Although the speed increase attributable to PSRT varies with the image generation environment, according to experiments comparing PSRT with standard ray-tracing, PSRT is 2.6 to 8.2 times faster than standard ray-tracing for 512 by 512 pixel images, maintaining the same visual image quality. It is true that images generated by this method may contain very small errors. However, such errors can be reduced and may be made visually negligible by using ICPS and the trees of ray-object intersection to check for similarities.

This paper describes a facsimile-based graphics editing system using handwritten mark recognition, and presents some experimental results with the system. In a manner different from usual graphics editors based on CRT displays and data tablets, only facsimiles are used as input and output devices in this system. As the first stage in processing, a graphic subject is first given as a set of line drawings and characters handwritten on a sheet of paper, and it is then input into the computer as a binary picture from a facsimile transmitter. Auxiliary editing information is input into the computer as handwritten marks or seal marks prepared on a separate sheet of paper. As the second stage, the marks are recognized and used to create a mark parameter list for the graphics editing. Third, referencing the mark parameter list, the graphics are expressed by using a set of graphic commands, and edited by the computer. Finally, a correct edited copy of the graphics is constructed by picture processing based on graphic commands, and it is output to a facsimile receiver. Very good results have been obtained for various kinds of hand-written graphics by using the system described here.

Incremental generation of straight lines and circular arcs is important in various fields such as graphic displays, digital plotters, and numerical control systems. An improved algorithm of incremental curve generation called a modified displacement comparison method (MDCM) is proposed.