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PTZ camera network calibration from moving people in sports broadcasts

机译:运动广播中移动人员的PTZ摄像机网络校准

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摘要

In sports broadcasts, networks consisting of pan-tilt-zoom (PTZ) cameras usually exhibit very wide baselines, making standard matching techniques for camera calibration very hard to apply. If, additionally, there is a lack of texture, finding corresponding image regions becomes almost impossible. However, such networks are often set up to observe dynamic scenes on a ground plane. Corresponding image trajectories produced by moving objects need to fulfill specific geometric constraints, which can be leveraged for camera calibration. We present a method which combines image trajectory matching with the self-calibration of rotating and zooming cameras, effectively reducing the remaining degrees of freedom in the matching stage to a 2D similarity transformation. Additionally, lines on the ground plane are used to improve the calibration. In the end, all extrinsic and intrinsic camera parameters are refined in a final bundle adjustment. The proposed algorithm was evaluated both qualitatively and quantitatively on four different soccer sequences.
机译:在体育广播中,由水平倾斜变焦(PTZ)摄像机组成的网络通常显示出非常宽的基线,因此很难应用用于摄像机校准的标准匹配技术。另外,如果缺少纹理,则几乎不可能找到相应的图像区域。但是,通常将此类网络设置为在地平面上观察动态场景。由移动物体产生的相应图像轨迹需要满足特定的几何约束,可以将其用于相机校准。我们提出了一种将图像轨迹匹配与旋转和缩放相机的自校准相结合的方法,可有效地将匹配阶段的剩余自由度降低到2D相似度转换。此外,接地平面上的线用于改善校准。最后,在最终的束调整中优化所有外部和固有摄像机参数。该算法在四个不同的足球序列上进行了定性和定量评估。

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