Motion detection of vehicles based on FPGA

Menezes, Gilliano G. S.; Silva-Filho, Abel G.

doi:10.1109/spl.2010.5483022

Cited by 9 publications

(7 citation statements)

References 3 publications

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“…Many methods for motion detection have already been proposed. They have been classified [1]- [3] into three major categories: background subtraction, [4], [5] temporal differencing [6] , [7] and optical flow [8], [9]. Further, motion detection methods have been recently classified into matching methods, energy-based methods, and gradient methods.…”

Section: Related Workmentioning

confidence: 99%

A Real-Time Implementation of Moving Object Action Recognition System Based on Motion Analysis

Sehairi

Benbouchama²,

Chouireb

2017

IJEEI

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This paper proposes a PixelStreams-based FPGA implementation of a real-time system that can detect and recognize human activity using Handel-C. In the first part of our work, we propose a GUI programmed using Visual C++ to facilitate the implementation for novice users. Using this GUI, the user can program/erase the FPGA or change the parameters of different algorithms and filters. The second part of this work details the hardware implementation of a real-time video surveillance system on an FPGA, including all the stages, i.e., capture, processing, and display, using DK IDE. The targeted circuit is an XC2V1000 FPGA embedded on Agility's RC200E board. The PixelStreams-based implementation was successfully realized and validated for real-time motion detection and recognition.

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Section: Related Workmentioning

confidence: 99%

A Real-Time Implementation of Moving Object Action Recognition System Based on Motion Analysis

Sehairi

Benbouchama²,

Chouireb

2017

IJEEI

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“…This is the drawback of using background subtraction algorithm. [2] developed FPGA based hardware for motion detection of vehicles on transit road. Experimental result shows that hardware based system performs 7.5 times faster than normal software based approaches.…”

Section: Literature Surveymentioning

confidence: 99%

“…Video surveillance is a key technology for fight against [3]. Video surveillance system for motion detection is a security device that is installed in building to detect unauthorized movement in restricted area [2]. Motion can be detected by measuring the change in speed or vector of an object.…”

mentioning

confidence: 99%

A Review on Motion Detection Techniques

Kumbhar¹,

Bhaskar²

2017

IJTSRD

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Motion detection is the process of detecting moving objects in background images. Motion detection plays a fundamental role in any object tracking or vide surveillance algorithm. The reliability with which potential foreground objects in movement can be identified, directly impacts on the efficiency and performance level achievable by subsequent processing stages of tracking or object recognition. The syst automatically performs a task and gives alert to security in an area. This paper represents review on Motion detection is an essential for many video applications such as video surveillance, military reconnaissance, and robotics. Most of these applications demand low power consumption, compact and lightweight design, and high speed computation platform for processing image data in real time.

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“…In the paper [38] a rather simple vehicle motion detection algorithm was reported. It was based on foreground object detection.…”

Section: Vehicle Detectionmentioning

confidence: 99%

Real-time hardware–software embedded vision system for ITS smart camera implemented in Zynq SoC

Kryjak

Komorkiewicz

Gorgon

2016

J Real-Time Image Proc

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The article demonstrates the usefulness of heterogeneous System on Chip (SoC) devices in smart cameras used in intelligent transportation systems (ITS). In a compact, energy efficient system the following exemplary algorithms were implemented: vehicle queue length estimation, vehicle detection, vehicle counting and speed estimation (using multiple virtual detection lines), as well as vehicle type (local binary features and SVM classifier) and colour (k-means classifier and YCbCr colourspace analysis) recognition. The solution exploits the hardwaresoftware architecture, i.e. the combination of reconfigurable resources and the efficient ARM processor. Most of the modules were implemented in hardware, using Verilog HDL, taking full advantage of the possible parallelization and pipeline, which allowed to obtain real-time image processing. The ARM processor is responsible for executing some parts of the algorithm, i.e. high-level image processing and analysis, as well as for communication with the external systems (e.g. traffic lights controllers). The demonstrated results indicate that modern SoC systems are a very interesting platform for advanced ITS systems and other advanced embedded image processing, analysis and recognition applications.Keywords Intelligent Transportation Systems Á Hardware-software image processing (Zynq SoC) Á Vehicle queue length estimation Á Vehicle detection Á Vehicle type and colour recognition

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Motion detection of vehicles based on FPGA

Cited by 9 publications

References 3 publications

A Real-Time Implementation of Moving Object Action Recognition System Based on Motion Analysis

A Real-Time Implementation of Moving Object Action Recognition System Based on Motion Analysis

A Review on Motion Detection Techniques

Real-time hardware–software embedded vision system for ITS smart camera implemented in Zynq SoC

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