Background subtraction algorithm for moving object detection in FPGA

Programmable embedded media server based video surveillance system is prevalent as it has the capability to accommodate large network of cameras. The implementation of a wide range of programmable security analytics application in PCbased platform demands high processing bandwidth and highend hardware specification requirements. This is due to insufficient compute resource by multicore CPU in performing some of the computationally intensive analytics operations at acceptable data rates. This paper presents a platform design considerations for programmable video analytics solving compute intensive video data processing leading to cost-efficient embedded platform solution. Our experimental analysis covers PC-based processing pipeline analysis for CPU resources to be used as design input for processing data offloading between multicore CPU and FPGA. The result identifies the processing bottleneck in PC-based media server with video analytics processing component consumes 81% of the total CPU processing cycles. This leads to the exploration of the PCI Express capability in FPGA for system solution as a transfer medium between these computing units.

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“…This functionality could be changed to other different algorithms such as fall detection, intrusion detection or plate number recognition [9].…”

Section: Video Analyticsmentioning

confidence: 99%

Real-time multiple video streams processing on PC-based FPGA platform

Mohd

Karuppiah

Chong

et al. 2012

Proceedings of 2012 2nd International Conference on Computer Science and Network Technology

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“…These methods of hardware based motion detection reported in literature differ from each other due to design methodologies/approaches and design tool chains used. Based on design methodologies, various hardware based methods can be categorized as general purpose processor based approach, digital signal processor (DSP) based approach [24][25][26], complex programmable logic device (CPLD) based approach [27], application specific integrated circuit (ASIC) based approach [28,29], FPGA based hardware design approach [30][31][32][33][34][35][36][37][38][39][40][41][42][43][44][45][46][47][48][49], and FPGA based hardware/software co-design approach [50][51][52]. From design tool-chain perspective, the differences can be based on the use of VHDL/Verilog, high level hardware description language like Handle-C or SystemC, MATLAB-Simulink software, an Embedded Development kit, and a System Generator tool.…”

Section: Introductionmentioning

confidence: 99%

FPGA-Based Real-Time Motion Detection for Automated Video Surveillance Systems

2016

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Design of automated video surveillance systems is one of the exigent missions in computer vision community because of their ability to automatically select frames of interest in incoming video streams based on motion detection. This research paper focuses on the real-time hardware implementation of a motion detection algorithm for such vision based automated surveillance systems. A dedicated VLSI architecture has been proposed and designed for clustering-based motion detection scheme. The working prototype of a complete standalone automated video surveillance system, including input camera interface, designed motion detection VLSI architecture, and output display interface, with real-time relevant motion detection capabilities, has been implemented on Xilinx ML510 (Virtex-5 FX130T) FPGA platform. The prototyped system robustly detects the relevant motion in real-time in live PAL (720ˆ576) resolution video streams directly coming from the camera.

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“…In an attempt to minimize the amount of time the system takes to determine whether or not an object is present, thereby increasing the overall productivity of the plant, an algorithm that can satisfactorily handle the tasks is preferred. As such, the background subtraction based algorithm [1] is suggested for this particular object detection method as it is not a computationally expensive algorithm and it also presents suitably high performance in terms of its accuracy. In this paper, we propose the implementation of an efficient object presence/absence detection system on FPGA that can be employed in the manufacturing industry.…”

Section: Introductionmentioning

confidence: 99%

“…This technique allows moving objects to be detected by taking the point-by-point absolute difference of the current image and a background image which must be acquired when there are no moving objects in the scene. Essentially, the concept behind the background subtraction approach is to find the mobbing objects by subtracting the current frame (pixel by pixel for increased accuracy) from a reference image called the background [1]. Seeing that in the manufacturing industry, the objects themselves are being continuously moved whilst the background remains unchanged, this method can be implemented.…”

Section: Introductionmentioning

confidence: 99%