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Improving performance of background subtraction on mobile devices: a parallel approach

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Abstract

Real-time detection of moving objects in a resource-constrained environment, such as a personal mobile device, is a challenging task. Nowadays, cameras of cell phones and other mobile devices produce high-resolution videos. In addition, possible camera motion which is inherent to mobile devices adds further complexity to the image processing. Real-time analysis of those videos can be performed using optimized versions of the background subtraction methods. The focus of this work is an efficient implementation of background subtraction using dual-mode single Gaussian model with age on Android platform. Several optimizations were applied: parallelization through RenderScript framework, block processing and grayscale transformation of pixels, and memory transfer and footprint reduction. Implemented algorithm was evaluated using multiple test scenarios on two different platforms. We observed speedups up to 6 times over the reference sequential implementation, real time performance of 50 FPS for 640 \(\times\) 480 videos and 20.7 FPS for 1280 \(\times\) 720 videos. Comparative analysis with state-of-the-art methods on CDNet 2014 PTZ category showed good F1-measure. The obtained results are carefully discussed.

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Authors and Affiliations

  1. Computer Engineering and Informatics, School of Electrical Engineering, University of Belgrade, Belgrade, Serbia

    Marko Mišić, Petar Kovačev & Milo Tomašević

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  1. Marko Mišić
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  2. Petar Kovačev
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  3. Milo Tomašević
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Correspondence to Marko Mišić.

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This work has been partially funded by the Ministry of Education, Science and Technological Development of the Republic of Serbia (III44009 and TR32047). The authors gratefully acknowledge the financial support.

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Mišić, M., Kovačev, P. & Tomašević, M. Improving performance of background subtraction on mobile devices: a parallel approach. J Real-Time Image Proc 19, 275–286 (2022). https://doi.org/10.1007/s11554-021-01184-x

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