基于鲁棒字典构建与更新的激光光斑检测

Zhihua Wang, Yongri Piao, Minglu Jin
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引用次数: 0

摘要

在激光笔交互系统中,激光光斑检测是最重要的技术之一,而该领域的大部分挑战都与交互系统的不同背景和实时性有关。本文提出了一种基于背景减法稀疏模型的鲁棒字典构建和更新算法。为了控制动态背景,首先,我们确定背景是否有变化;如果这是真的,新的背景可以直接添加到字典配置中;否则,我们将对背景进行在线累积平均以更新字典。提出的激光光斑检测字典构建与更新算法对不同背景和噪声具有较强的鲁棒性,可以实时实现。大量的实验结果证实了该方法在检测误差和实时性方面的优越性能。
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Laser Spot Detection Using Robust Dictionary Construction and Update
In laser pointer interaction systems, laser spot detection is one of the most important technologies, and most of the challenges in this area are related to the varying backgrounds, and the real-time performance of the interaction system. In this paper, we present a robust dictionary construction and update algorithm based on a sparse model of background subtraction. In order to control dynamic backgrounds, first, we determine whether there is a change in the backgrounds; if this is true, the new background can be directly added to the dictionary configurations; otherwise, we run an online cumulative average on the backgrounds to update the dictionary. The proposed dictionary construction and update algorithm for laser spot detection, is robust to the varying backgrounds and noises, and can be implemented in real time. A large number of experimental results have confirmed the superior performance of the proposed method in terms of the detection error and real-time implementation.
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