A Fast and Sub-Pixel Detector for Grid-Like Target in Camera Calibration

Lejun Shen, Zhun-Yu Ke
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引用次数: 0

Abstract

Sub-pixel detection of target points is the performance bottleneck in camera calibration. Traditional algorithms are computational expensive or low precision when we do camera calibration in sport video analysis. In this paper, we propose a new algorithm to detect the grid-like target (i.e. tennis court in TV broadcasting). It has 3 parts: (1) color histogram based interested point classifier making our method faster; (2) sub-pixel refinement by non-linear least squares method improving the accuracy; (3) extended line scan using interested point as the start/end point finding the final line parameters. Results indicate that our detector is faster (<9ms), more accurate and requires less memory than Hough based algorithms if target is grid-like: "straight lines link together".
一种快速亚像素的摄像机标定类网格目标检测器
目标点的亚像素检测是摄像机标定中的性能瓶颈。在运动视频分析中,传统的摄像机标定算法计算量大,精度低。本文提出了一种新的网格状目标(即电视广播中的网球场)检测算法。它包括三个部分:(1)基于颜色直方图的兴趣点分类器,使我们的方法更快;(2)采用非线性最小二乘法进行亚像素细化,提高精度;(3)以感兴趣点为起点/终点的扩展线扫描,找到最终的线参数。结果表明,如果目标是“直线连接在一起”的网格状目标,我们的检测器比基于Hough的算法更快(<9ms),更准确,并且需要更少的内存。
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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