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.
4 citations
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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
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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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References
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TL;DR: To achieve real-time performance with high resolution video streams, a dedicated hardware architecture with streamlined dataflow and memory access reduction schemes are developed to implement a video segmentation unit used for embedded automated video surveillance systems.
Abstract: This paper presents the implementation of a video segmentation unit used for embedded automated video surveillance systems. Various aspects of the underlying segmentation algorithm are explored and modifications are made with potential improvements of segmentation results and hardware efficiency. In addition, to achieve real-time performance with high resolution video streams, a dedicated hardware architecture with streamlined dataflow and memory access reduction schemes are developed. The whole system is implemented on a Xilinx field-programmable gate array platform, capable of real-time segmentation with VGA resolution at 25 frames per second. Substantial memory bandwidth reduction of more than 70% is achieved by utilizing pixel locality as well as wordlength reduction. The hardware platform is intended as a real-time testbench, especially for observations of long term effects with different parameter settings.
56 citations
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TL;DR: This study reports on a preliminary estimation of the human-horse interaction through the analysis of the heart rate variability (HRV) in both human and animal by using the dynamic time warping (DTW) algorithm.
Abstract: This study reports on a preliminary estimation of the human-horse interaction through the analysis of the heart rate variability (HRV) in both human and animal by using the dynamic time warping (DTW) algorithm. Here, we present a wearable system for HRV monitoring in horses. Specifically, we first present a validation of a wearable electrocardiographic (ECG) monitoring system for horses in terms of comfort and robustness, then we introduce a preliminary objective estimation of the human-horse interaction. The performance of the proposed wearable system for horses was compared with a standard system in terms of movement artifact (MA) percentage. Seven healthy horses were monitored without any movement constraints. As a result, the lower amount of MA% of the wearable system suggests that it could be profitably used for reliable measurement of physiological parameters related to the autonomic nervous system (ANS) activity in horses, such as the HRV. Human-horse interaction estimation was achieved through the analysis of their HRV time series. Specifically, DTW was applied to estimate dynamic coupling between human and horse in a group of fourteen human subjects and one horse. Moreover, a support vector machine (SVM) classifier was able to recognize the three classes of interaction with an accuracy greater than 78%. Preliminary significant results showed the discrimination of three distinct real human-animal interaction levels. These results open the measurement and characterization of the already empirically-proven relationship between human and horse.
33 citations
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TL;DR: In this paper, the stability and electronic structure of MoS 2 monolayers are influenced by alloying, i.e., by substitution of the transition metal Mo by W and Nb and of the chalcogen S by Se.
Abstract: Layered transition-metal dichalcogenides have extraordinary electronic properties, which can be easily modified by various means. Here, we have investigated how the stability and electronic structure of MoS 2 monolayers is influenced by alloying, i.e., by substitution of the transition metal Mo by W and Nb and of the chalcogen S by Se. While W and Se incorporate into the MoS 2 matrix homogeneously, forming solid solutions, the incorporation of Nb is energetically unstable and results in phase separation. However, all three alloying atoms change the electronic band structure significantly. For example, a very small concentration of Nb atoms introduces localized metallic states, while Mo 1 - x W x S 2 and MoS 2 - y Se y alloys exhibit spin-splitting of the valence band of strength that is in between that of the pure materials. Moreover, small, but evident spin-splitting is introduced in the conduction band due to the symmetry breaking. Therefore, transition-metal dichalcogenide alloys are interesting candidates for optoelectronic and spintronic applications.
31 citations
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TL;DR: This paper proposes a Time-Synchronized Application-level MAC protocol (TSAM) capable of operating on top of existing 802.11 protocols using commodity off-the-shelf hardware and shows how TSAM is able to improve throughput and provide bounded delay.
Abstract: In recent years, there has been an increase in video surveillance systems in public and private environments due to a heightened sense of security. The next generation of surveillance systems will be able to annotate video and locally coordinate the tracking of objects while multiplexing hundreds of video streams in real-time. In this paper, we present OmniEye, a wireless distributed real-time surveillance system composed of wireless smart cameras. OmniEye is comprised of custom-designed smart camera nodes called DSPcams that communicate using an IEEE 802.11 mesh network. These cameras provide wide-area coverage and local processing with the ability to direct a sparse number of high-resolution pan, tilt and zoom (PTZ) cameras that can home onto targets of interest. Each {\em DSPcam} performs local processing to help classify events and pro-actively draw an operator's attention when necessary.In video-streaming applications, maintaining high network utilization is required in order to maximize image quality as well as the number of cameras. Our experiments show that by using the standard 802.11 DCF MAC protocol for communication, the system does not scale beyond 5-6 cameras while each camera is streaming at 1 Mbps. Also, we see high levels of jitter in video transmissions. This performance degrades further for multi-hop scenarios due to the presence of hidden nodes. In order to improve the system's scalability and reliability, we propose a Time-Synchronized Application-level MAC protocol (TSAM) capable of operating on top of existing 802.11 protocols using commodity off-the-shelf hardware. Through analysis and experimental validation, we show how TSAM is able to improve throughput and provide bounded delay. Unlike traditional CSMA-based systems, TSAM gracefully degrades in a fair manner so that existing streams can still deliver data.
31 citations
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TL;DR: 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.
Abstract: 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 (720 × 576) resolution video streams directly coming from the camera.
15 citations
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