In ball sports, understanding spatial information, such as player positions and open spaces, is crucial for making informed decisions regarding when and where to pass the ball. This study develops a novel training support system for improving players' spatial cognition and skill levels. The support system employed a 360° camera positioned near the viewpoint of the passer and recreating the scene via a virtual reality device. By superimposing the dominant region (an area the target player can reach faster than any other player) and the space in which a pass can be received onto 360° images, the scenario obtained by the passer’s viewpoint can be replayed from an arbitrary line of sight. Furthermore, the system provides additional spatial information that evolves based on player movements in real time. This study proposes a novel method for extracting and visualizing spatial information and presents examples of its applications.
This paper describes a smart method to model bobsleigh track surface. On real bobsleigh tracks, the cross-sectional
shape is generally rectangular in the strait section, and in contrast, circular and banked in the curve section. In the first
step, three-dimensional shapes of track surface are generated automatically based on these two kinds of cross-sectional
shapes along the track centerline. In the second step, the most suitable parameters of track surface modeling, which
consist of triangular patches is decided by evaluating the smoothness of sliding in dynamic simulation with Unity.
In this paper, a system for automated real-time tracking of a figure skater moving on an ice rink by using PTZ cameras is
presented. This system is intended for support in training of skating, for example, as a tool for recording and evaluation
of his/her motion performances. In the processing procedure of the system, an ice rink region is extracted first from a
video image by region growing method, then one of hole components in the obtained rink region is extracted as a skater
region. If there exists no hole component, a skater region is estimated from horizontal and vertical intensity projections
of the rink region. Each camera is automatically panned and/or tilted so as to keep the skater region on almost the center
of the image, and also zoomed so as to keep the height of the skater region within an appropriate range. In the
experiments using 5 practical video images of skating, it was shown that the extraction rate of the skater region was
almost 90%, and tracking with camera control was successfully done for almost all of the cases used here.
This paper proposes a basic feature for quantitative measurement and evaluation of group behavior of persons. This feature called 'dominant region' is a kind of sphere of influence for each person in the group. The dominant region is defined as a region in where the person can arrive earlier than any other persons and can be formulated as Voronoi region modified by replacing the distance function with a time function. This time function is calculated based on a computational model of moving ability of the person. As an application of the dominant region, we present a motion analysis system of soccer games. The purpose of this system is to evaluate the teamwork quantitatively based on movement of all the players in the game. From experiments using motion pictures of actual games, it is suggested that the proposed feature is useful for measurement and evaluation of group behavior in team sports. This basic feature may be applied to other team ball games, such as American football, basketball, handball and water polo.
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