Real-time door detection for indoor autonomous vehicle

Zhihao He; Ming Zhu

doi:10.1117/12.2281651

21 July 2017 Real-time door detection for indoor autonomous vehicle

Zhihao He, Ming Zhu

Proceedings Volume 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017); 104200V (2017) https://doi.org/10.1117/12.2281651
Event: Ninth International Conference on Digital Image Processing (ICDIP 2017), 2017, Hong Kong, China

Abstract

Indoor Autonomous Vehicle(IAV) is used in many indoor scenes. Such as hotels and hospitals. Door detection is a key issue to guide the IAV into rooms. In this paper, we consider door detection in the use of indoor navigation of IAV. Since real-time properties are important for real-world IAV, the detection algorithm must be fast enough. Most monocular-camera based door detection model need a perfect detection of the four line segments of the door or the four corners. But in many situations, line segments could be extended or cut off. And there could be many false detected corners. And few of them can distinguish doors from door-like objects with door-like shape effectively. We proposed a 2-D vision model of the door that is made up of line segments. The number of parts detected is used to determine the possibility of a door. Our algorithm is tested on a database of doors.1 The robustness and real-time are verified. The precision is 89.4%. Average time consumed for processing a 640x320 figure is 44.73ms.

Citation Download Citation

Zhihao He and Ming Zhu "Real-time door detection for indoor autonomous vehicle", Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 104200V (21 July 2017); https://doi.org/10.1117/12.2281651

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