瞳孔检测图像传感器设计参数优化框架

Gernot Fiala, Zhenyu Ye, C. Steger
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引用次数: 0

摘要

机器视觉系统(MVS)使用图像传感器来处理和分析图像数据。根据应用的不同,图像传感器参数的配置也不同。但是,对于特定的产品生成或产品线,有些参数是固定的。其中一个参数是像素间距,即从一个物理像素到另一个物理像素的距离。在这项工作中,我们引入了一个框架,该框架允许优化用于瞳孔检测的图像传感器的设计参数。我们比较了两种不同像素设计的图像传感器模型,生成了不同位深和分辨率的图像。利用生成的图像和瞳孔检测算法对设计参数进行了评估。此外,对已有的瞳孔检测数据集进行了扩展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Framework for Image Sensor Design Parameter Optimization for Pupil Detection
Machine vision systems (MVS) use image sensors to process and analyze image data. Depending on the application, the image sensor parameters are configured differently. However, some parameters are fixed for a specific product generation or product line. One of these parameters is the pixel pitch, the distance from one physical pixel to another. In this work, we introduce a framework, which allows to optimize design parameters of image sensors for pupil detection. We compare 2 different image sensor models with different pixel designs and generate images with different bit depths and resolutions. An evaluation of the design parameters is done with the generated images and a pupil detection algorithm. Furthermore, an existing pupil detection dataset is extended.
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