Automated vehicle detection is a research field in constant evolution due to the new technological advances and security requirements demanded by the current intelligent transportation systems. For these reasons, in this paper we present a vision-based vehicle detection and tracking pipeline, which is able to run on an iPhone in real time. An approach based on smartphone cameras supposes a versatile solution and an alternative to other expensive and complex sensors on the vehicle, such as LiDAR or other range-based methods. A multi-scale proposal and simple geometry consideration of the roads based on the vanishing point are combined to overcome the computational constraints. Our algorithm is tested on a publicly available road dataset, thus demonstrating its real applicability to ADAS or autonomous driving.


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    Title :

    A Real-Time Multi-scale Vehicle Detection and Tracking Approach for Smartphones


    Contributors:


    Publication date :

    2015-09-01


    Size :

    1485400 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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