We developed an automatic tracking system camera for TV program production that is capable of making stable shots by detecting the performers? facial positions. This system can make tracking shots as specified by the user, by using a subject detection module in which input images are simultaneously processed by several image-processing algorithms installed in PCs on a local network. The robot camera is driven with a feedback control for correcting face positions in an image and a speed control for responding to the subject?s movement. An experiment on automatic shooting of moving performers confirmed that this camera system can shoot viewer-friendly images, i.e., images without large vibrations that affect a subject's position in an image.

We have developed an intelligent robot camera system to support the production of broadcast television programs. The objective was to develop a system that automatically shoots scenes that are completely natural as if taken by an experienced camera operator, and that enables a single operator to control multiple cameras at the same time. We have developed an automatic program production system that is composed of several network-connected robot cameras programmed to mimic the shooting and camerawork techniques of professional camera operators. In this paper we give an overview of a prototype system using a new subject detection system and three robot cameras that are linked over a network and present a detailed summary of the trial results.

No abstract available.

In our paper of Supercomputing '88, an overview of V-Pascal, an automatic vectorizing compiler for Pascal, was presented with focus on its Version 1. In that paper, as one of those higher functions to be added to Version 2 V-Pascal, vector-mode execution of nonnummeric operations such as relational database operations and nonnumeric data manipulations was considered. This paper describes the actual results we have obtained. These results are important in that a new vista has been opened up for vector supercomputers which are originally designed solely for high-speed manipulations of scientific numerical data.

A detailed anatomy of the automatic vectorizing compiler V-Pascal (Version 1, now operational) is given. With no language extensions, V-Pascal efficiently vectorizes the whole of arbitrarily given multiply nested for loops using the mechanism of vector indirect addressing. Higher functions of V-Pascal, such as vectorization of WHILE-DO and recursive calls, vectorization of relational operations on relational databases defined by record-type data structures, and automatic parallel decomposition for multiprocessor environments, are considered for Version 2, which is currently in the process of design and implementation.>

The nonlinear interpolation of functions of very many variables is discussed. Deterministic termwise assessment of a prohibitively large number of terms naturally leads to a choice of random sampling from these numerous terms. After introduction of an appropriate higher order interpolation formula, a working algorithm is established by the Monte Carlo method. Numerical examples are also given.

The feasibility of Monte Carlo linear extrapolation of multivariable functions is discussed. The method considered is a modified version of the Monte Carlo method for linear interpolation. An effective truncation procedure is introduced, which not only economizes the machine time to a greet extent, but also serves for the purpose of variance reduction. A few examples were tested, all of which have shown that the method is promising.