Facial recognition using simulated prosthetic pixelized vision
Facial recognition using simulated prosthetic pixelized vision
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DOI：
10.1167/iovs.03-0341
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发表时间：
2003-11-01
影响因子：
4.4
通讯作者：
Dagnelie, G
中科院分区：
文献类型：
--
作者：
Thompson, RW;Barnett, GD;Dagnelie, G
目的评估一种使用非连续圆形磷光体的模拟像素化义肢视觉模型，以测试磷光体和网格参数对面部识别的影响。 方法：使用视频耳机观看由四张人脸组成的参考集，然后通过包含 10 X 10 到 32 X 32 点的方形像素化网格观看其中一张人脸的部分遮挡图像。网格大小、网点大小、间隙宽度、网点丢失率和灰度分辨率分别根据标准测试条件的不同而变化，共有 16 种测试条件。所有测试首先在 99% 对比度下进行，然后在 12.5% 对比度下重复。受试者的识别速度和表现受到所有刺激参数的影响。受试者在所有高对比度测试中都达到了非常高的面部识别准确率，只有 70% 随机点缺失和两个灰度级的网格除外。在低对比度测试中，除了最不利的网格参数：网格总面积小于目标图像的 17%、70% 滤除、四个或更少的灰度级以及 40.5 弧分的间隙之外，受试者在其他所有网格参数下都能达到显著的面部识别准确率。在困难的测试条件下，高对比度试验中出现了明显的组队效应，而在随后的低对比度试验中则出现了更微妙的计时练习效应。这些研究结果表明，使用粗糙的像素化网格进行可靠的人脸识别是可以学会的，即使使用粗糙的视觉假肢也有可能实现。
PURPOSE. To evaluate a model of simulated pixelized prosthetic vision using noncontiguous circular phosphenes, to test the effects of phosphene and grid parameters on facial recognition.METHODS. A video headset was used to view a reference set of four faces, followed by a partially averted image of one of those facesviewed through a square pixelizing grid that contained 10 X 10 to 32 X 32 dots separated by gaps. The grid size, dot size, gap width, dot dropout rate, and gray-scale resolution were varied separately about a standard test condition, for a total of 16 conditions. All tests were first performed at 99% contrast and then repeated at 12.5% contrast.RESULTS. Discrimination speed and performance were influenced by all stimulus parameters. The subjects achieved highly significant facial recognition accuracy for all high-contrast tests except for grids with 70% random dot dropout and two gray levels. In low-contrast tests, significant facial recognition accuracy was achieved for all but the most adverse grid parameters: total grid area less than 17% of the target image, 70% dropout, four or fewer gray levels, and a gap of 40.5 arcmin. For difficult test conditions, a pronounced teaming effect was noticed during high-contrast trials, and a more subtle practice effect on timing was evident during subsequent low-contrast trials.CONCLUSIONS. These findings suggest that reliable face recognition with crude pixelized grids can be learned and may be possible, even with a crude visual prosthesis.