Paper Info
Title
RISE: An Automated Framework for Real-Time Intelligent Video Surveillance on FPGA.
Abstract
This paper proposes RISE, an automated Reconfigurable framework for real-time background subtraction applied to Intelligent video SurveillancE. RISE is devised with a new streaming-based methodology that adaptively learns/updates a corresponding dictionary matrix from background pixels as new video frames are captured over time. This dictionary is used to highlight the foreground information in each video frame. A key characteristic of RISE is that it adaptively adjusts its dictionary for diverse lighting conditions and varying camera distances by continuously updating the corresponding dictionary. We evaluate RISE on natural-scene vehicle images of different backgrounds and ambient illuminations. To facilitate automation, we provide an accompanying API that can be used to deploy RISE on FPGA-based system-on-chip platforms. We prototype RISE for end-to-end deployment of three widely-adopted image processing tasks used in intelligent transportation systems: License Plate Recognition (LPR), image denoising/reconstruction, and principal component analysis. Our evaluations demonstrate up to 87-fold higher throughput per energy unit compared to the prior-art software solution executed on ARM Cortex-A15 embedded platform.
Year
DOI
Venue
2017
10.1145/3126549
ACM Trans. Embedded Comput. Syst.
Keywords
Field
DocType
Background subtraction, Data streaming, Intelligent video surveillance, License plate recognition, Reconfigurable computing
Background subtraction,Computer vision,Computer science,Field-programmable gate array,Image processing,Automation,Real-time computing,Software,Pixel,Artificial intelligence,Intelligent transportation system,Reconfigurable computing
Journal
Volume
Issue
ISSN
16
5
1539-9087
Citations 
PageRank 
References 
1
0.35
17
Authors
3
Name
Order
Citations
PageRank
Bita Darvish Rouhani19913.53
Azalia Mirhoseini223818.68
Farinaz Koushanfar33055268.84