21 April 2016 Real-time multiple objects tracking on Raspberry-Pi-based smart embedded camera
Aziz Dziri, Marc Duranton, Roland Chapuis
Author Affiliations +
Abstract
Multiple-object tracking constitutes a major step in several computer vision applications, such as surveillance, advanced driver assistance systems, and automatic traffic monitoring. Because of the number of cameras used to cover a large area, these applications are constrained by the cost of each node, the power consumption, the robustness of the tracking, the processing time, and the ease of deployment of the system. To meet these challenges, the use of low-power and low-cost embedded vision platforms to achieve reliable tracking becomes essential in networks of cameras. We propose a tracking pipeline that is designed for fixed smart cameras and which can handle occlusions between objects. We show that the proposed pipeline reaches real-time processing on a low-cost embedded smart camera composed of a Raspberry-Pi board and a RaspiCam camera. The tracking quality and the processing speed obtained with the proposed pipeline are evaluated on publicly available datasets and compared to the state-of-the-art methods.
© 2016 SPIE and IS&T 1017-9909/2016/$25.00 © 2016 SPIE and IS&T
Aziz Dziri, Marc Duranton, and Roland Chapuis "Real-time multiple objects tracking on Raspberry-Pi-based smart embedded camera," Journal of Electronic Imaging 25(4), 041005 (21 April 2016). https://doi.org/10.1117/1.JEI.25.4.041005
Published: 21 April 2016
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CITATIONS
Cited by 14 scholarly publications.
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KEYWORDS
Cameras

Sensors

Detection and tracking algorithms

Image processing

Imaging systems

Video

Digital signal processing

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