scholarly journals A MOBILE CROWDSOURCING SYSTEM FOR FOOTBALL MATCH LIVE VIDEO STREAMING

2018 ◽  
Vol 6 ◽  
pp. 1083-1088
Author(s):  
Georgi Iliev
Keyword(s):  
Real Time ◽  
Video Streaming ◽  
Video Processing ◽  
High Speed ◽  
Collaborative Work ◽  
Video Data ◽  
Mobile Crowdsourcing ◽  
Football Match ◽  
Service Oriented ◽  
Parallel Video Processing

Mobile crowdsourcing is a fast-growing emerging approach whereby large groups of mobile users are engaged in a collaborative work on performing a particular task or using its results. This paper presents a concept for the development of a mobile crowdsourcing system with extended capabilities for real-time broadcasting and receiving amateur football match video. It is designed to resolve the problem of possible delays and the overload of a system and to accelerate the process of big video data transmission. The proposed system is based on a service-oriented, three-layer cloud architecture and a specialized mobile video streaming application. The architecture includes a main server, infrastructure of scalable multi-parallel video processing engine and an auxiliary server for synchronizing real-time information, which significantly facilitates the handling of user requests with minimal cost and at a high speed. The concept is realized in the Footlikers platform as a basic client-server, WOWZA streaming engine, deployed on an Amazon EC2 cloud machine and a simple sync-server. The results of the program realization of the developed system prototype are presented, regarding football game video steaming intended for amateur football competitions based and organized in France, Belgium and Luxembourg.

scholarly journals SIAT: A Distributed Video Analytics Framework for Intelligent Video Surveillance

Symmetry ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 911 ◽  
Author(s):  
Md Azher Uddin ◽  
Aftab Alam ◽  
Nguyen Anh Tu ◽  
Md Siyamul Islam ◽  
Young-Koo Lee
Keyword(s):  
Distributed Computing ◽  
Real Time ◽  
Video Surveillance ◽  
Video Processing ◽  
Large Scale ◽  
Distributed Processing ◽  
Content Management ◽  
Video Data ◽  
Video Analytics ◽  
Intelligent Video Surveillance

In recent years, the amount of intelligent CCTV cameras installed in public places for surveillance has increased enormously and as a result, a large amount of video data is produced every moment. Due to this situation, there is an increasing request for the distributed processing of large-scale video data. In an intelligent video analytics platform, a submitted unstructured video undergoes through several multidisciplinary algorithms with the aim of extracting insights and making them searchable and understandable for both human and machine. Video analytics have applications ranging from surveillance to video content management. In this context, various industrial and scholarly solutions exist. However, most of the existing solutions rely on a traditional client/server framework to perform face and object recognition while lacking the support for more complex application scenarios. Furthermore, these frameworks are rarely handled in a scalable manner using distributed computing. Besides, existing works do not provide any support for low-level distributed video processing APIs (Application Programming Interfaces). They also failed to address a complete service-oriented ecosystem to meet the growing demands of consumers, researchers and developers. In order to overcome these issues, in this paper, we propose a distributed video analytics framework for intelligent video surveillance known as SIAT. The proposed framework is able to process both the real-time video streams and batch video analytics. Each real-time stream also corresponds to batch processing data. Hence, this work correlates with the symmetry concept. Furthermore, we introduce a distributed video processing library on top of Spark. SIAT exploits state-of-the-art distributed computing technologies with the aim to ensure scalability, effectiveness and fault-tolerance. Lastly, we implant and evaluate our proposed framework with the goal to authenticate our claims.

The Design of Real-Time and High-Speed Video Processing Platform for Aerial UAV Based on DM642

2014 ◽  
Vol 1061-1062 ◽  
pp. 1186-1189
Author(s):  
Ming Zhe Wei ◽  
Wan Wei Tang
Keyword(s):  
Real Time ◽  
Video Processing ◽  
High Speed ◽  
Rapid Development ◽  
Processing System ◽  
Video Signal ◽  
Good Effect ◽  
Time Data ◽  
Spatial Interference ◽  
On Chip

With the rapid development of aerial UAV (Unmanned Aerial Vehicle), the design of real-time data acquisition and transmission system for the video signal has a new applied field. It is different from traditional video acquisition and processing system, aerial video signal has the problems of screen jitter and spatial interference. The processing algorithm of aerial UAV airborne video signal is put forward in the paper, and the platform of high speed procession is constructed based on chip TMS320DM642, and get a good effect.

scholarly journals GPU Accelerated real-time Melanoma Detection

2018 ◽  
Vol 7 (3) ◽  
pp. 1208
Author(s):  
Ajai Sunny Joseph ◽  
Elizabeth Isaac
Keyword(s):  
Real Time ◽  
Video Processing ◽  
Processing Technique ◽  
Video Data ◽  
Image Processing Technique ◽  
Processing Unit ◽  
Central Processing ◽  
Melanoma Detection ◽  
Real Time Analysis ◽  
Graphical Processing

Melanoma is recognized as one of the most dangerous type of skin cancer. A novel method to detect melanoma in real time with the help of Graphical Processing Unit (GPU) is proposed. Existing systems can process medical images and perform a diagnosis based on Image Processing technique and Artificial Intelligence. They are also able to perform video processing with the help of large hardware resources at the backend. This incurs significantly higher costs and space and are complex by both software and hardware. Graphical Processing Units have high processing capabilities compared to a Central Processing Unit of a system. Various approaches were used for implementing real time detection of Melanoma. The results and analysis based on various approaches and the best approach based on our study is discussed in this work. A performance analysis for the approaches on the basis of CPU and GPU environment is also discussed. The proposed system will perform real-time analysis of live medical video data and performs diagnosis. The system when implemented yielded an accuracy of 90.133% which is comparable to existing systems.  

An Intelligent High-Frame-Rate Video Logging System for Abnormal Behavior Analysis

2011 ◽  
Vol 23 (1) ◽  
pp. 53-65 ◽  
Author(s):  
Yao-DongWang ◽  
◽  
Idaku Ishii ◽  
Takeshi Takaki ◽  
Kenji Tajima ◽  
...  
Keyword(s):  
Real Time ◽  
Video Processing ◽  
High Speed ◽  
Vision System ◽  
Video Recording ◽  
Frame Rate ◽  
Abnormal Behavior ◽  
High Frame Rate ◽  
Abnormal Behavior Detection ◽  
Abnormal Behaviors

This paper introduces a high-speed vision system called IDP Express, which can execute real-time image processing and High-Frame-Rate (HFR) video recording simultaneously. In IDP Express, 512×512 pixel images from two camera heads and the processed results on a dedicated FPGA (Field Programmable Gate Array) board are transferred to standard PC memory at a rate of 1000 fps or more. Owing to the simultaneous HFR video processing and recording, IDP Express can be used as an intelligent video logging system for long-term high-speed phenomenon analysis. In this paper, a real-time abnormal behavior detection algorithm was implemented on IDP-Express to capture HFR videos of crucial moments of unpredictable abnormal behaviors in high-speed periodic motions. Several experiments were performed for a high-speed slider machine with repetitive operation at a frequency of 15 Hz and videos of the abnormal behaviors were automatically recorded to verify the effectiveness of our intelligent HFR video logging system.

Real-Time Acoustic and Pressure Characterization of Two-Phase Flow for Quality Control of Expanded Polystyrene Injection Molding Processes

2015 ◽  
Vol 138 (5) ◽  
Author(s):  
James N. Magarian ◽  
Robert D. White ◽  
Douglas M. Matson
Keyword(s):  
Injection Molding ◽  
Real Time ◽  
High Speed ◽  
Expanded Polystyrene ◽  
Video Data ◽  
Injection Molding Process ◽  
Molding Process ◽  
Two Phase ◽  
Acoustic Data ◽  
Acoustic Standing Wave

A method is proposed for real-time process monitoring for expanded polystyrene (EPS) injection molding systems. The method employs measurement of two variables: vacuum pressure in the EPS supply hose and phase difference between two points along an acoustic standing wave generated within the EPS flow path. High-speed videography is utilized as a secondary means of monitoring the injection molding process. Video data are correlated with pressure and acoustic data to substantiate those variables’ validity as indicators of intended molding system performance. Data show recorded parameter curve shapes to be indicative of key injection molding milestone events, such as valve timing and changes in flow regime.

Design of Image Processing System Based on FPGA

2011 ◽  
Vol 403-408 ◽  
pp. 1281-1284
Author(s):  
Guo Sheng Xu
Keyword(s):  
Real Time ◽  
Data Storage ◽  
High Speed ◽  
Design Method ◽  
Processing System ◽  
Video Data ◽  
Scanning System ◽  
Time Data ◽  
The Real ◽  
Video Data Compression

To speed up the image acquisition and make full use of effective information, a design method of CCD partial image scanning system is presented. The system achieves to functions of the high -speed data collection, the high -speed video data compression the real time video data Network Transmission and the real time compression picture data storage. the data processed was transferred to PC through USB2.0 real-time to reconstruct defects microscopic images. Experiments show that the system has stable performance, real-time data transmission and high quality images, feasible by adopting the algorithm and scheme proposed in this paper.

scholarly journals A High Speed Architecture for Lifting-based 2-D Cohen-Daubechies-Feauveau (5,3) Discrete Wavelet Transform used in JPEG2000

2017 ◽  
Vol 6 (1) ◽  
pp. 24 ◽  
Author(s):  
Mohammad Rafi Lone ◽  
Najeed- Ud-Din
Keyword(s):  
Real Time ◽  
Video Processing ◽  
High Speed ◽  
Parallel Implementation ◽  
Critical Path ◽  
Low Complexity ◽  
Discrete Wavelet ◽  
Throughput Optimization ◽  
Xilinx Fpga ◽  
Parallel Fashion

For real-time applications, efficient VLSI implementation of DWT is desired. In this paper, DWT architecture based on retiming for pipelining and unfolding is presented. The architecture is based on lifting one-dimensional Cohen-Daubechies-Feauveau (CDF) (5,3) wavelet filter, which is easily extended to 2-D implementation. It consists of low complexity and easily repeatable components. This paper is focused on the critical path minimization and throughput optimization at the same time. The architecture has been implemented on Virtex 6 Xilinx FPGA platform. The implementation results show that the critical path is minimized four to five times, while throughput is doubled, making the overall architecture approximately ten times faster when compared with the conventional lifting-based DWT architecture. Further with parallel implementation, the throughput has doubled without any increase in number of row buffers, implying that the architecture is memory efficient as well. The even and odd rows of the image are scanned in parallel fashion. To perform the 2-D DWT transform of an image of size 15 Megapixels, it takes 16.86 ms, which implies 59 images of that size can be processed in one second. This can be utilized for real-time video processing applications even for high resolution videos.

scholarly journals Real-Time Video Image Processing based on Kerr Soliton Krystal Microcombs

2021 ◽  
Author(s):  
mengxi tan ◽  
xingyuan xu ◽  
David Moss
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Video Processing ◽  
High Speed ◽  
Autonomous Driving ◽  
Next Generation ◽  
Video Signals ◽  
Image And Video Processing ◽  
Massively Parallel Processing ◽  
Photonic Processing

Advanced image processing will be crucial for emerging technologies such as autonomous driving, where the requirement to quickly recognize and classify objects under rapidly changing, poor visibility environments in real time will be needed. Photonic technologies will be key for next-generation signal and information processing, due to their wide bandwidths of 10’s of Terahertz and versatility. Here, we demonstrate broadband real time analog image and video processing with an ultrahigh bandwidth photonic processor that is highly versatile and reconfigurable. It is capable of massively parallel processing over 10,000 video signals simultaneously in real time, performing key functions needed for object recognition, such as edge enhancement and detection. Our system, based on a soliton crystal Kerr optical micro-comb with a 49GHz spacing with >90 wavelengths in the C-band, is highly versatile, performing different functions without changing the physical hardware. These results highlight the potential for photonic processing based on Kerr microcombs for chip-scale fully programmable high-speed real time video processing for next generation technologies.

scholarly journals Real-time video image processing based on optical Kerr microcombs

2021 ◽  
Author(s):  
David Moss
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Video Processing ◽  
High Speed ◽  
Autonomous Driving ◽  
Next Generation ◽  
Video Signals ◽  
Image And Video Processing ◽  
Massively Parallel Processing ◽  
Photonic Processing

<p>Advanced image processing will be crucial for emerging technologies such as autonomous driving, where the requirement to quickly recognize and classify objects under rapidly changing, poor visibility environments in real time will be needed. Photonic technologies will be key for next-generation signal and information processing, due to their wide bandwidths of 10’s of Terahertz and versatility. Here, we demonstrate broadband real time analog image and video processing with an ultrahigh bandwidth photonic processor that is highly versatile and reconfigurable. It is capable of massively parallel processing over 10,000 video signals simultaneously in real time, performing key functions needed for object recognition, such as edge enhancement and detection. Our system, based on a soliton crystal Kerr optical micro-comb with a 49GHz spacing with >90 wavelengths in the C-band, is highly versatile, performing different functions without changing the physical hardware. These results highlight the potential for photonic processing based on Kerr microcombs for chip-scale fully programmable high-speed real time video processing for next generation technologies.</p>

scholarly journals A Service-Oriented Real-Time Communication Scheme for AUTOSAR Adaptive Using OPC UA and Time-Sensitive Networking

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2337
Author(s):  
Anna Arestova ◽  
Maximilian Martin ◽  
Kai-Steffen Jens Hielscher ◽  
Reinhard German
Keyword(s):  
Real Time ◽  
High Speed ◽  
Data Exchange ◽  
Autonomous Driving ◽  
Transportation Industry ◽  
Vehicle Engineering ◽  
Client Server ◽  
Critical Data ◽  
Service Oriented ◽  
Cost Efficient

The transportation industry is facing major challenges that come along with innovative trends like autonomous driving. Due to the growing amount of network participants, smart sensors, and mixed-critical data, scalability and interoperability have become key factors of cost-efficient vehicle engineering. One solution to overcome these challenges is the AUTOSAR Adaptive software platform. Its service-oriented communication methodology allows a standardized data exchange that is not bound to a specific middleware protocol. OPC UA is a communication standard that is well-established in modern industrial automation. In addition to its Client–Server communication pattern, the newly released Publish–Subscribe (PubSub) architecture promotes scalability. PubSub is designed to work in conjunction with Time-Sensitive Networking (TSN), a collection of standards that add real-time aspects to standard Ethernet networks. TSN allows services with different requirements to share a single physical network. In this paper, we specify an integration approach of AUTOSAR Adaptive, OPC UA, and TSN. It combines the benefits of these three technologies to provide deterministic high-speed communication. Our main contribution is the architecture for the binding between Adaptive Platform and OPC UA. With a prototypical implementation, we prove that a combination of OPC UA Client–Server and PubSub qualifies as a middleware solution for service-oriented communication in AUTOSAR.

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