中国邮电高校学报(英文版) ›› 2016, Vol. 23 ›› Issue (5): 88-96.doi: 10.1016/S1005-8885(16)60062-6

• Others • 上一篇    

Vision-based positioning system

宋美娜 欧阳中洪 鄂海红 宋俊德 Zhao Xuejun   

  1. 1. 北京邮电大学计算机学院
    2. 北京邮电大学
    3.
    4. 北京邮电大学电子工程学院
  • 收稿日期:2015-12-14 修回日期:2016-09-27 出版日期:2016-10-30 发布日期:2016-10-26
  • 通讯作者: 宋美娜 E-mail:mnsong@gmail.com
  • 基金资助:
    the National Key Project of Scientific and Technical Supporting Programs of China

Vision-based positioning system

Song Meina , Ou Zhonghong, E Haihong, Song Junde, Zhao Xuejun   

  • Received:2015-12-14 Revised:2016-09-27 Online:2016-10-30 Published:2016-10-26
  • Contact: Mei-Na Song E-mail:mnsong@gmail.com
  • Supported by:
    the National Key Project of Scientific and Technical Supporting Programs of China

摘要: Conventional outdoor navigation systems are usually based on orbital satellites, e.g., global positioning system (GPS) and global navigation satellite system (GLONASS). The latest advances from wearable, e.g., BaiduEye and Google Glass, have enabled new approaches to leverage information from the surrounding environment. For example, they enable the change from passively receiving information to actively requesting information. Thus, such changes might inspire brand new application scenarios that were not possible before. In this work, we propose a vision-based navigation system based on wearable like Baidu Eye. We discuss the associated challenges and propose potential solutions for each of them. The system utilizes crowd sensing to collect and build a traffic signpost database for positioning reference. Then it leverages context information, such as cell identification (Cell ID), signal strength, and altitude combined with traffic sign detection and recognition to enable real-time positioning. A hybrid cloud architecture is proposed to enhance the capability of sensing devices (SD) to realize the proposed vision.

关键词: vision-based, positioning system, wearable, machine vision

Abstract: Conventional outdoor navigation systems are usually based on orbital satellites, e.g., global positioning system (GPS) and global navigation satellite system (GLONASS). The latest advances from wearable, e.g., BaiduEye and Google Glass, have enabled new approaches to leverage information from the surrounding environment. For example, they enable the change from passively receiving information to actively requesting information. Thus, such changes might inspire brand new application scenarios that were not possible before. In this work, we propose a vision-based navigation system based on wearable like Baidu Eye. We discuss the associated challenges and propose potential solutions for each of them. The system utilizes crowd sensing to collect and build a traffic signpost database for positioning reference. Then it leverages context information, such as cell identification (Cell ID), signal strength, and altitude combined with traffic sign detection and recognition to enable real-time positioning. A hybrid cloud architecture is proposed to enhance the capability of sensing devices (SD) to realize the proposed vision.

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