A trajectory-based ball detection and tracking system with applications to shooting angle and velocity estimation in basketball videos

Bodhisattwa Chakraborty, S. Meher
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引用次数: 20

Abstract

This paper presents a system to automatically analyse a basketball long-shot using trajectory-based ball tracking method from a basketball video sequence. The accuracy of a long-shot in a basketball game is mostly dependent on the ball throwing angle and the velocity at which the ball is to be thrown. The proposed system detects and tracks the ball in a basketball long-shot sequence by exploiting the trajectory information of the ball. The ball motion characteristics are used to determine the ball trajectory. The candidate trajectories are generated from a set of ball candidates in each frame. The trajectory-based ball tracking minimised the rate of error of ball tracking in the video which occurs due to occlusion and merging of the ball image with other objects in the frame, distortion of the ball image due to ball and camera motion and the presence of many moving objects in the foreground and background in the video. The ball locations verified by the tracking results are then used to estimate the ball throwing angle and the throwing velocity. The experiments show encouraging results for videos with dynamic background and different illumination conditions.
基于轨迹的球检测与跟踪系统及其在篮球视频中投篮角度和速度估计中的应用
提出了一种利用基于轨迹的球跟踪方法对篮球视频序列中的远射镜头进行自动分析的系统。在篮球比赛中,远投的准确性主要取决于投球的角度和投球的速度。该系统利用球的运动轨迹信息对篮球远射序列中的球进行检测和跟踪。球的运动特性用于确定球的运动轨迹。候选轨迹由每帧中的一组候选球生成。基于轨迹的球跟踪最小化了视频中球跟踪的错误率,这种错误率是由于球图像与帧中的其他物体的遮挡和合并,由于球和摄像机的运动以及视频中前景和背景中存在许多运动物体而导致的球图像失真。然后利用跟踪结果验证的球位置来估计球的投掷角度和投掷速度。对动态背景和不同光照条件下的视频,实验结果令人鼓舞。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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