足球视频镜头分类与球场区域检测

Soccer video shot classification and playfield zone detection

目的足球视频镜头和球场区域是足球视频事件检测的必要条件,对于足球视频语义分析具有重要作用。针对现有镜头分类方法的不足,提出识别足球视频镜头类型的波动检测法。方法该方法使用一个滑动窗口在视频帧图像中滑动,记录滑动窗口内球场像素比例在远镜头阈值上下的波动次数,根据波动次数判断镜头类型。对于足球场地区域分类,提出使用视频图像中球场区域的左上角和右上角点的位置关系识别球场区域类型的方法,该方法使用高斯混合模型识别出球场,根据球场在帧图像中左右边界坐标的高低判断球场区域类型,方法简单高效。结果本文提出的两种方法与现有的分类方法相比,在准确率和召回率方面具有较大提高,检测效率高,可以满足实时性要求。结论本文方法解决了传统滑动窗口法无法正确识别球场倾斜角度过大的帧图像,降低了传统球场区域检测方法依赖球场线检测而导致的准确率不高的问题。

Objective Soccer video shots and field areas are the necessary conditions for soccer video event detection, which plays an important role in the semantic analysis of soccer videos. Method A new fluctuation detection method is proposed to classify the soccer video shot to address the shortcomings of existing shot classification methods. This method adopts a slid- ing window to slide in the video frame image. The fluctuation times of the field pixel ratio that crosses the threshold ratio of the in-field shot are recorded, and then the shot type is judged according to the fluctuation number. A novel approach is also proposed to identify the playfield zone type by GMM （Gaussian Mixture Model） , which is simple and efficient, by ap- plying the position relationship between the upper left corner and upper right corner. Result Experimental results show that the two methods exhibit significant improvement in accuracy recall rate, high detection efficiency, and can meet the real-time requirements, unlike existing classification methods. Conclusion The proposed methods can address the problem of the traditional sliding window method that incorrectly identifies the large frame image of the field inclination angle. These methods can also solve the problem of the traditional field area detection method relying on the field line detection, which leads to a low accuracy rate.