高效最稳定极值区域(MSER)跟踪

M. Donoser, H. Bischof
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引用次数: 330

摘要

本文介绍了一种局部最大稳定极值区检测器的跟踪方法。构件树是一种有效的数据结构,可以在准线性时间内计算mser。结果表明,该树能够管理所需的跟踪数据。我们表明,通过MSER跟踪,单个MSER检测的计算时间可以提高4到10倍。采用加权特征向量进行数据关联,提高了跟踪的稳定性。此外,组件树支持向后跟踪,这进一步提高了鲁棒性。在多种场景下对该算法进行了评价。此外,我们还演示了三种不同的应用,车牌、人脸和纸上纤维的跟踪,在所有三种情况下都显示了提高的速度和稳定性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficient Maximally Stable Extremal Region (MSER) Tracking
This paper introduces a tracking method for the well known local MSER (Maximally Stable Extremal Region) detector. The component tree is used as an efficient data structure, which allows the calculation of MSERs in quasi-linear time. It is demonstrated that the tree is able to manage the required data for tracking. We show that by means of MSER tracking the computational time for the detection of single MSERs can be improved by a factor of 4 to 10. Using a weighted feature vector for data association improves the tracking stability. Furthermore, the component tree enables backward tracking which further improves the robustness. The novel MSER tracking algorithm is evaluated on a variety of scenes. In addition, we demonstrate three different applications, tracking of license plates, faces and fibers in paper, showing in all three scenarios improved speed and stability.
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