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用深度替代强度并进行实时光幻视渲染:低视力条件下的视觉导航

Substituting depth for intensity and real-time phosphene rendering: visual navigation under low vision conditions.

作者信息

Lieby Paulette, Barnes Nick, McCarthy Chris, Liu Nianjun, Dennett Hugh, Walker Janine G, Botea Viorica, Scott Adele F

机构信息

NICTA Canberra Research Laboratory, Tower A, 7 London Circuit, Canberra ACT 2600, Locked Bag 8001, Canberra ACT 2601, Australia.

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:8017-20. doi: 10.1109/IEMBS.2011.6091977.

Abstract

Navigation and way finding including obstacle avoidance is difficult when visual perception is limited to low resolution, such as is currently available on a bionic eye. Depth visualisation may be a suitable alternative. Such an approach can be evaluated using simulated phosphenes with a wearable mobile virtual reality kit. In this paper, we present two novel approaches: (i) an implementation of depth visualisation; and, (ii) novel methods for rapid rendering of simulated phosphenes with an empirical comparison between them. Our new software-based method for simulated phosphene rendering shows large speed improvements, facilitating the display in real-time of a large number of phosphenes with size and brightness dependent on pixel intensity, and with customised output dynamic range. Further, we describe the protocol, navigation environment and system used for visual navigation experiments to evaluate the use of depth on low resolution simulations of a bionic eye perceptual experience. Results for these experiments show that a depth-based representation is effective for navigation, and shows significant advantages over intensity-based approaches when overhanging obstacles are present. The results of the experiments were reported in [1], [2].

摘要

当视觉感知限于低分辨率时,诸如目前在仿生眼上所具备的那种,包括避障在内的导航和路径寻找都很困难。深度可视化可能是一种合适的替代方法。可以使用可穿戴移动虚拟现实套件通过模拟光幻视来评估这种方法。在本文中,我们提出了两种新颖的方法:(i)深度可视化的实现;以及(ii)用于快速渲染模拟光幻视的新颖方法,并对它们进行实证比较。我们基于软件的模拟光幻视渲染新方法显示出大幅的速度提升,便于实时显示大量根据像素强度具有大小和亮度且具有定制输出动态范围的光幻视。此外,我们描述了用于视觉导航实验的协议、导航环境和系统,以评估在仿生眼感知体验的低分辨率模拟中深度的使用情况。这些实验的结果表明基于深度的表示对于导航是有效的,并且在存在悬垂障碍物时比基于强度的方法具有显著优势。实验结果已在[1]、[2]中报道。

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