Digital images are found in several sizes and are easily displayed on a computer screen using techniques that can reduce their dimensions. Moreover, algorithms are used to process images to perform several tasks, for instance, detection of people. Recently, gigapixel images emerged, providing a huge amount of data; however, algorithms for people detection have been usually tested only on regular size images. This paper presents an impact analysis of the resolution reduction in the detection of people in gigapixel images. People detectors were trained with the INRIA and CALTECH data sets and results show that, although gigapixel images provide a huge false positive rate, the resolution reduction significantly decreases the number of bounding boxes and false positives, however, increasing the rate of missing people.

中文翻译：

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降维对千兆像素图像中人物检测方法的影响研究

数字图像有多种尺寸，可以使用缩小尺寸的技术轻松显示在计算机屏幕上。此外，算法用于处理图像以执行多项任务，例如人员检测。最近，出现了十亿像素的图像，提供了大量的数据；然而，人检测算法通常只在常规尺寸的图像上进行过测试。本文介绍了对千兆像素图像中人物检测中分辨率降低的影响分析。人员检测器使用 INRIA 和 CALTECH 数据集进行训练，结果表明，虽然十亿像素图像提供了巨大的误报率，但分辨率的降低显着减少了边界框和误报的数量，然而，增加了失踪人员的比率。