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Sensors 2016, 16(10), 1721;

Generic Dynamic Environment Perception Using Smart Mobile Devices

Computer Science Department, Technical University of Cluj Napoca, 28 Memorandumului Street, Cluj Napoca 400114, Romania
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Received: 28 July 2016 / Revised: 4 October 2016 / Accepted: 12 October 2016 / Published: 17 October 2016
(This article belongs to the Section Physical Sensors)
Full-Text   |   PDF [7658 KB, uploaded 17 October 2016]   |  


The driving environment is complex and dynamic, and the attention of the driver is continuously challenged, therefore computer based assistance achieved by processing image and sensor data may increase traffic safety. While active sensors and stereovision have the advantage of obtaining 3D data directly, monocular vision is easy to set up, and can benefit from the increasing computational power of smart mobile devices, and from the fact that almost all of them come with an embedded camera. Several driving assistance application are available for mobile devices, but they are mostly targeted for simple scenarios and a limited range of obstacle shapes and poses. This paper presents a technique for generic, shape independent real-time obstacle detection for mobile devices, based on a dynamic, free form 3D representation of the environment: the particle based occupancy grid. Images acquired in real time from the smart mobile device’s camera are processed by removing the perspective effect and segmenting the resulted bird-eye view image to identify candidate obstacle areas, which are then used to update the occupancy grid. The occupancy grid tracked cells are grouped into obstacles depicted as cuboids having position, size, orientation and speed. The easy to set up system is able to reliably detect most obstacles in urban traffic, and its measurement accuracy is comparable to a stereovision system. View Full-Text
Keywords: obstacle detection; occupancy grid; monocular vision; advanced driving assistance system; mobile device obstacle detection; occupancy grid; monocular vision; advanced driving assistance system; mobile device

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Supplementary material

  • Externally hosted supplementary file 1
    Description: The application that implements the algorithms described in the paper can be downloaded from the following link: . A text file describing the steps required for installing and using the application can be downloaded from .

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Danescu, R.; Itu, R.; Petrovai, A. Generic Dynamic Environment Perception Using Smart Mobile Devices. Sensors 2016, 16, 1721.

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