FPGA-Based Smart Camera System for Real-Time Automated Video Surveillance
29 Jun 2017-pp 533-544
TL;DR: The design and implementation of an FPGA-based smart camera system for automated video surveillance that meets the real-time requirements of video surveillance applications while aiming atFPGA resource reduction is presented.
Abstract: Automated video surveillance is a rapidly evolving area and has been gaining importance in the research community in recent years due to its capabilities of performing more efficient and effective surveillance by employing smart cameras. In this article, we present the design and implementation of an FPGA-based smart camera system for automated video surveillance. The complete system is prototyped on Xilinx ML510 FPGA platform and meets the real-time requirements of video surveillance applications while aiming at FPGA resource reduction. The implemented smart camera system is capable of automatically performing real-time motion detection, real-time video history generation, real-time focused region extraction, real-time filtering of frames of interest, and real-time object tracking of identified target with automatic purposive camera movement. The system is designed to work in real-time for live color video streams of standard PAL (720 × 576) resolution, which is the most commonly used video resolution for current generation surveillance systems. The implemented smart camera system is also capable of processing HD resolution video streams in real-time.
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TL;DR: The focal point of this work is to develop an intelligent camera surveillance system which englobes the key functionalities of existing surveillance systems and integrates a novel and advanced object displacement detection feature to provide more security by determining if an object has been displaced by an intruder.
Abstract: The focal point of this work is to develop an intelligent camera surveillance system which englobes the key functionalities of existing surveillance systems. Other than regular functionalities such as motion detection, object detection, face recognition and counting people, it also integrates a novel and advanced object displacement detection feature to provide more security by determining if an object has been displaced by an intruder. When people are detected, a counting module displays the number of persons present in the surveillance area. A face recognition module distinguishes between authorised and unauthorised users. This biometric functionality reduces false alarms which makes the system more robust. An object detection module detects certain valuable objects such as handbags, laptops and smartphones. Also, images and short video recordings are stored on the cloud. Furthermore, the system introduces innovative real-time notification approaches for surveillance systems such as WhatsApp messages and phone calls, in addition to SMS and emails. Thus, this system is reliable and meets the aim of a modern intelligent surveillance system by combining multiple approaches to detect intrusions and to inform users effectively.
6 citations
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...The authors state that their work meets the requirements of surveillance systems [32]....
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TL;DR: A global vision of the issues published in the Electronic magazine and their importance, advances and developments that have been particularly relevant for subsequent research are established.
Abstract: The contributions of researchers at a global level in the journal Electronics in the period 2012–2020 are analyzed. The objective of this work is to establish a global vision of the issues published in the Electronic magazine and their importance, advances and developments that have been particularly relevant for subsequent research. The magazine has 15 thematic sections and a general one, with the programming of 385 special issues for 2020–2021. Using the Scopus database and bibliometric techniques, 2310 documents are obtained and distributed in 14 thematic communities. The communities that contribute to the greatest number of works are Power Electronics (20.13%), Embedded Computer Systems (13.59%) and Internet of Things and Machine Learning Systems (8.11%). A study of the publications by authors, affiliations, countries as well as the H index was undertaken. The 7561 authors analyzed are distributed in 87 countries, with China being the country of the majority (2407 authors), followed by South Korea (763 authors). The H-index of most authors (75.89%) ranges from 0 to 9, where the authors with the highest H-Index are from the United States, Denmark, Italy and India. The main publication format is the article (92.16%) and the review (5.84%). The magazine publishes topics in continuous development that will be further investigated and published in the near future in fields as varied as the transport sector, energy systems, the development of new broadband semiconductors, new modulation and control techniques, and more.
1 citations
01 Jan 2023
TL;DR: In this paper , a survey on 3D hand detection and tracking and their applications as a natural user interface to control the computer with hand movements and gestures is presented. But the focus is on the 3D mouse and keyboard.
Abstract: 3D hand detection and tracking algorithms has increased research interests in computer vision, pattern recognition, and human-computer interfacing. It is greatly inspired by the emerging technologies like RGBD camera, depth sensors and processing architecture. Therefore, this paper presents a survey on recent works on 3D hand detection and tracking and their applications as a natural user interface to control the computer with hand movements and gestures. It examines the literature in terms of 1) 3D hand capturing techniques used like RGBD cameras, depth sensors, 2) processing with different image processing and computer vision algorithms and their hardware implementation 3) and applications in human computer interfacing for realization of the system. While the emphasis is on 3D mouse and keyboard, the related findings and future challenges are also discussed for practitioners.
TL;DR: A novel and systematic approach for dynamic allocation of tasks in a video surveillance system using smart cameras and based on Cloud/Fog architecture is proposed, guaranteeing the best solution optimizing power consumption and communication cost over the system.
Abstract: In this paper we propose a novel and systematic approach for dynamic allocation of tasks in a video surveillance system using smart cameras and based on Cloud/Fog architecture. Tracking tasks arrive in the system in a random way and must be assigned to the available devices (cameras, Fog nodes and the Cloud). Our approach guarantees the best solution optimizing power consumption and communication cost over the system. The proposed methods uses an integer programming model and its effectiveness is shown on an application example.
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...For example, [1] describes the design and the...
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...However, these requirements are becoming increasingly difficult to satisfy in the case of multimedia applications such as video surveillance one in smart environment, for instance, such as buildings or cities is a recent trend [1]....
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References
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TL;DR: The proposed, designed and implemented system robustly tracks the target object present in the scene in real time for standard PAL (720 × 576) resolution color video and automatically controls camera movement in the direction determined by the movement of the tracked object.
Abstract: The design of smart video surveillance systems is an active research field among the computer vision community because of their ability to perform automatic scene analysis by selecting and tracking the objects of interest In this paper, we present the design and implementation of an FPGA-based standalone working prototype system for real-time tracking of an object of interest in live video streams for such systems In addition to real-time tracking of the object of interest, the implemented system is also capable of providing purposive automatic camera movement (pan-tilt) in the direction determined by movement of the tracked object The complete system, including camera interface, DDR2 external memory interface controller, designed object tracking VLSI architecture, camera movement controller and display interface, has been implemented on the Xilinx ML510 (Virtex-5 FX130T) FPGA Board Our proposed, designed and implemented system robustly tracks the target object present in the scene in real time for standard PAL (720 × 576) resolution color video and automatically controls camera movement in the direction determined by the movement of the tracked object
8 citations
TL;DR: The top level description of a complete automated video surveillance system is presented along with the elaboration of different challenges/issues involved in its design and implementation, a comparative analysis of design methodologies and existing FPGA platforms, and details of various primary input/output interfaces required for designing smart automated video Surveillance systems for future.
Abstract: Because of increasing terrorist activities, the resolution of video cameras and the number of cameras deployed for surveillance are increasing exponentially – producing huge amount of video data. Manual analysis of this large volume of video data by human operators for crime scene and forensic analysis is neither reliable nor scalable. This has generated enormous interest in research activities related to automation of video surveillance systems which allows real-time automatic extraction and analysis of information from live incoming video streams and enables automatic detection and tracking of targets without human intervention. To meet the real-time requirements of automated video surveillance systems, very different technologies and design methodologies have been used in literature. These range from use of General Purpose Processors (GPPs) or special purpose Digital Signal Processors (DSPs) or Graphics Processing Units (GPUs) to Application Specific Integrated Circuits (ASICs) or Applications Specific Instruction Set Processors (ASIPs) or even programmable logic devices like Field Programmable Gate Arrays (FPGAs). FPGAs provide real-time performance that is hard to achieve with GPPs/DSPs, limit the extensive design work, time, and cost required for ASICs, and allow algorithmic changes in later stages of system development. Due to these features FPGAs are being increasingly used for prototyping automated video surveillance system quickly. In this paper we present the top level description of a complete automated video surveillance system along with the elaboration of different challenges/issues involved in its design and implementation, a comparative analysis of design methodologies and existing FPGA platforms, complete design flow for prototyping the FPGA-based automated video surveillance system, and details of various primary input/output interfaces required for designing smart automated video surveillance systems for future.
7 citations
TL;DR: The proposed VLSI architecture robustly detects the changes in a video stream in real time at 25 frames per second in gray scale CIF size video and its implementation on Virtex-IIPro FPGA platform is presented.
Abstract: Change detection is one of the several important problems in the design of any automated video surveillance system. Appropriate selection of frames of significant changes can minimize the communication and processing overheads for such systems. This research presents the design of a VLSI architecture for change detection in a video sequence and its implementation on Virtex-IIPro FPGA platform. Clustering-based scheme is used for change detection. The proposed system is designed to meet the real-time requirements of video surveillance applications. It robustly detects the changes in a video stream in real time at 25 frames per second (fps) in gray scale CIF size video.
6 citations
TL;DR: The designed VLSI architecture has been integrated with different input/output video interfaces in order to realize the complete system, which is capable of tracking the moving target object in real-time in PAL (720x576) resolution live video stream directly coming from the camera.
Abstract: This paper presents the design and implementation of a dedicated hardware (VLSI) architecture for real-time object tracking. In order to realize the complete system, the designed VLSI architecture has been integrated with different input/output video interfaces. These video interfaces along with the designed object tracking VLSI architecture have been coded using VHDL, simulated using ModelSim, and synthesized using Xilinx ISE tool chain. A working prototype of complete object tracking system has been implemented on Xilinx ML510 (Virtex-5 FX130T) FPGA board. The implemented system is capable of tracking the moving target object in real-time in PAL (720x576) resolution live video stream directly coming from the camera. Additionally, the implemented system also provides the real-time desired camera movement to follow the tracked object over a larger area.
5 citations
01 Oct 2011
TL;DR: This paper proposes the hardware accelerator capable of detecting real time changes in a scene, which uses clustering based change detection scheme, and is designed and simulated using VHDL and implemented on Xilinx XUP Virtex-IIPro FPGA board.
Abstract: Smart Cameras are important components in Human Computer Interaction. In any remote surveillance scenario,
smart cameras have to take intelligent decisions to select frames of significant changes to minimize communication and
processing overhead. Among many of the algorithms for change detection, one based on clustering based scheme was
proposed for smart camera systems. However, such an algorithm could achieve low frame rate far from real-time
requirements on a general purpose processors (like PowerPC) available on FPGAs. This paper proposes the hardware
accelerator capable of detecting real time changes in a scene, which uses clustering based change detection scheme. The
system is designed and simulated using VHDL and implemented on Xilinx XUP Virtex-IIPro FPGA board. Resulted
frame rate is 30 frames per second for QVGA resolution in gray scale.
2 citations