We aim to realize new image expressions—3D position analysis and computer graphics (CG) synthesis—by using multiple pan-tilt cameras for live broadcasts. For this purpose, a camera calibration technique is needed that is accurate over a wide space such as a stadium and has high operability. We thus propose a method to accurately calibrate multiple pan-tilt cameras that can be used in live broadcasts. This method enables cameras to be accurately calibrated over a wide space by using multiple calibration patterns and a system to be efficient prepared at a filming location. After the preparation, accurate camera parameters can be obtained in real time using the pan-tilt angles acquired from angle sensors in the camera platform. We showed the effectiveness of the proposed method through CG simulation and experiments using a real system. In addition, we developed a 3D ball tracking system that uses our calibration method.

We have developed a real-time ball tracking system that can be used for volleyball games. Although a number of methods for visual object tracking have been proposed, tracking a fast-moving ball is still a challenging task because of the motion blur and the occlusion. We thus use a complementary tracking scheme in which tracking processes for multiple cameras help each other sharing the 3D position of the ball. The ball on each camera is accurately tracked by predicting its position at the next frame. The 3D ball positions measured by the system can be used for drawing the trajectory CG of a ball and for calculating statistical data related to ball movement. Evaluation results obtained using actual volleyball video sequences showed that the system would be effective for visualizing ball trajectories in live volleyball broadcasts.

A handy system is presented for creating in real time a natural television image composed of a real scene and a computer graphics object. The light positions and colors (RGB values) in the real scene are estimated and then applied to the object by using simple equipment. Objective and subjective experiments demonstrated the effectiveness of this system. An enhanced algorithm is also presented that improves the accuracy of light estimation.

We have developed a robust method for estimating camera parameters for live TV production based on infrared markers whose feature-point extraction is simple and two-dimensional color histogram matching that considers the effects of specular reflection due to lighting. We first explain the principle of the proposed technique. We then present the results of a basic experiment for evaluating the accuracy of marker identification and the results of an image-compositing experiment using estimated camera parameters. We show that the proposed technique is effective based on those results.