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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/102595

    Title: 以智慧型手機與機器學習輔助提升視障同胞行走安全性
    Other Titles: Improving safety of walking for visually impaired people using smart phones and machine learning
    Authors: 黃詩雯;Huang, Shih-Wen
    Contributors: 淡江大學資訊工程學系碩士班
    Keywords: 群眾外包;機器學習;智慧型手機;視障;Crowdsourcing;Machine learning;Smartphone;Visually impaired
    Date: 2014
    Issue Date: 2015-05-04 09:59:40 (UTC+8)
    Abstract: 對於視障同胞而言,障礙物與階梯路段會增加行走的困難度,更可能導致意外跌倒。許多研究學者提出一些透過智慧型手機或是電腦視覺的方式,增進視障同胞的行走安全。在本篇論文中我們提出了一種替代的方案來達到相同的目標-也就是利用群眾外包的力量以及使用機器學習。具體來說,我們利用非視障同胞所使用的智慧型手機收集,三軸加速度數值與相對應的GPS地理座標。接著,將所得到的資料使用機器學習的技巧分析後,轉換成地形圖,並對室外階梯路段做標記。在視障同胞將地圖下載至智慧型手機後,我們所開發設計的Android App能夠監控視障同胞所處的室外位置,當視障同胞將要靠近階梯路段時,透過語音的方式做提醒。
    Visually impaired people have difficulty in walking freely because of the obstacles or the stairways along their walking paths, which can lead to accidental falls. Many researchers have devoted to promoting safe walking for visually impaired people by using smartphones and computer vision. In this research we propose an alternative approach to achieve the same goal – we take advantage of the power of crowdsourcing with machine learning. Specifically, by using smartphones carried by a vast amount of visually normal people, we can collect the tri-axial accelerometer data along with the corresponding GPS coordinates in large geographic areas. Then, machine learning techniques are used to analyze the data, turning them into a special topographic map in which the regions of outdoor stairways are marked. With the map installed in the smartphones carried by the visually impaired people, the Android App we developed can monitor their current outdoor locations and then enable an acoustic alert when they are getting close to the stairways.
    Appears in Collections:[Graduate Institute & Department of Computer Science and Information Engineering] Thesis

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