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Environment Description for Blind People

机译:盲人的环境描述

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摘要

Visual processing is very efficient, letting people to use vision as the first approach to get information about environment. For blind people that information must be complemented with another very powerful data collection: sounds. In order to complement the white stick sounds, the prototype HOLO-TECH gathers and segments video images and produces specific sounds to acknowledge about potential hazards. The underlaying model is based on a set of Neural Networks coordinated by an Expert System to make it possible to react to any new event in real time. This paper presents an outline of the model, the project and a test set to evaluate one of the Neural Networks specialized to detect and evaluate faces and other objects like cars. The main contribution of this work is automate the selection model for proper combination of information, discarding unnecessary data and defining the minimum precision requirements to fulfill the current goal.
机译:视觉处理非常有效,让人们使用视觉作为获取环境信息的第一种方法。对于盲人来说,信息必须与另一个非常强大的数据收集相辅相成:声音。为了补充白色棒的声音,原型Holo-Tech收集和区段视频图像并产生特定的声音,以确认潜在的危险。底层模型基于由专家系统协调的一组神经网络,以使其可以实时对任何新事件做出反应。本文介绍了模型,项目和测试集的轮廓,以评估专门检测和评估脸部和其他物体等物体的神经网络之一。这项工作的主要贡献是自动化选择模型,以便适当的信息组合,丢弃不必要的数据并定义满足当前目标的最低精度要求。

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