Parallel Video Processing Techniques for Surveillance Applications

2014 ◽  
Author(s):  
Leonidas Deligiannidis ◽  
Hamid R. Arabnia
Keyword(s):  
Video Processing ◽  
Parallel Video Processing ◽  
Processing Techniques ◽  
Surveillance Applications

scholarly journals Efficient Parallel Video Processing Techniques on GPU: From Framework to Implementation

2014 ◽  
Vol 2014 ◽  
pp. 1-19 ◽  
Author(s):  
Huayou Su ◽  
Mei Wen ◽  
Nan Wu ◽  
Ju Ren ◽  
Chunyuan Zhang
Keyword(s):  
Video Processing ◽  
Parallel Implementation ◽  
Parallel Architecture ◽  
Optimization Methods ◽  
Memory Bandwidth ◽  
Deblocking Filter ◽  
Parallel Video Processing ◽  
Speedup Ratio ◽  
Processing Techniques ◽  
Execution Order

Through reorganizing the execution order and optimizing the data structure, we proposed an efficient parallel framework for H.264/AVC encoder based on massively parallel architecture. We implemented the proposed framework by CUDA on NVIDIA’s GPU. Not only the compute intensive components of the H.264 encoder are parallelized but also the control intensive components are realized effectively, such as CAVLC and deblocking filter. In addition, we proposed serial optimization methods, including the multiresolution multiwindow for motion estimation, multilevel parallel strategy to enhance the parallelism of intracoding as much as possible, component-based parallel CAVLC, and direction-priority deblocking filter. More than 96% of workload of H.264 encoder is offloaded to GPU. Experimental results show that the parallel implementation outperforms the serial program by 20 times of speedup ratio and satisfies the requirement of the real-time HD encoding of 30 fps. The loss of PSNR is from 0.14 dB to 0.77 dB, when keeping the same bitrate. Through the analysis to the kernels, we found that speedup ratios of the compute intensive algorithms are proportional with the computation power of the GPU. However, the performance of the control intensive parts (CAVLC) is much related to the memory bandwidth, which gives an insight for new architecture design.

Unmanned Aerial Vehicle–Based Traffic Analysis: Methodological Framework for Automated Multivehicle Trajectory Extraction

2017 ◽  
Vol 2626 (1) ◽  
pp. 25-33 ◽  
Author(s):  
Muhammad Arsalan Khan ◽  
Wim Ectors ◽  
Tom Bellemans ◽  
Davy Janssens ◽  
Geert Wets
Keyword(s):  
Traffic Safety ◽  
Video Processing ◽  
Traffic Monitoring ◽  
Future Research ◽  
Methodological Framework ◽  
Vehicle Detection And Tracking ◽  
Potential Applications ◽  
Multiple Vehicles ◽  
Processing Techniques ◽  
Optimal Data Analysis

Unmanned aerial vehicles (UAVs), commonly referred to as drones, are one of the most dynamic and multidimensional emerging technologies of the modern era. This technology has recently found multiple potential applications within the transportation field, ranging from traffic surveillance applications to traffic network analysis. To conduct a UAV-based traffic study, extremely diligent planning and execution are required followed by an optimal data analysis and interpretation procedure. In this study, however, the main focus was on the processing and analysis of UAV-acquired traffic footage. A detailed methodological framework for automated UAV video processing is proposed to extract the trajectories of multiple vehicles at a particular road segment. Such trajectories can be used either to extract various traffic parameters or to analyze traffic safety situations. The proposed framework, which provides comprehensive guidelines for an efficient processing and analysis of a UAV-based traffic study, comprises five components: preprocessing, stabilization, georegistration, vehicle detection and tracking, and trajectory management. Until recently, most traffic-focused UAV studies have employed either manual or semiautomatic processing techniques. In contrast, this paper presents an in-depth description of the proposed automated framework followed by a description of a field experiment conducted in the city of Sint-Truiden, Belgium. Future research will mainly focus on the extension of the applications of the proposed framework in the context of UAV-based traffic monitoring and analysis.

scholarly journals Multimedia Image Processing Lab Experiment/Simulation

2020 ◽  
Vol 3 (1) ◽  
pp. 1-13
Author(s):  
Md Mamunur Rashid
Keyword(s):  
Image Processing ◽  
Video Compression ◽  
Video Processing ◽  
Multimedia Systems ◽  
Multimedia System ◽  
Image And Video Processing ◽  
Indexing And Retrieval ◽  
Video Indexing And Retrieval ◽  
Multimedia Image ◽  
Processing Techniques

Image Processing in Multimedia Applications treats a number of critical topics in multimedia systems, with respect to image and video processing techniques and their implementations. These techniques include the Image and video compression techniques and standards, and Image and video indexing and retrieval techniques. Image Processing is an important tool to develop a Multimedia system design.

PLAYER'S POSITIONAL DEPENDENCE OF FRACTAL BEHAVIORS IN A SOCCER GAME

Fractals ◽  
2006 ◽  
Vol 14 (01) ◽  
pp. 71-76 ◽  
Author(s):  
SANGRAK KIM
Keyword(s):  
Time Series ◽  
Video Processing ◽  
Fractal Dimensions ◽  
Two Dimensional ◽  
Severe Attack ◽  
Soccer Game ◽  
Relative Dominance ◽  
Processing Techniques

This paper describes fractal behaviors in a soccer game according to the player's position. It is quite important for us to characterize the fractal motion behaviors of the objects during the game. We obtained two-dimensional coordinates of the objects using standard video processing techniques from a computer soccer game. We calculated values of regularization dimensions of the time series to characterize their fractal behaviors. To see positional dependence, we averaged individual player's values over the same position in the same team. When a team is one-sidedly experiencing a severe attack, its defenders have higher fractal dimensions than those of the opponent's corresponding players. We propose a new measure of relative dominance in attack against the opponent team.

Hardware Efficient Hybrid Encoder for Video Surveillance Application

2020 ◽  
pp. 2150113
Author(s):  
Minesh Patel ◽  
Anand Darji
Keyword(s):  
Video Surveillance ◽  
Integrated Circuit ◽  
Video Processing ◽  
Signal To Noise Ratio ◽  
Scalable Video Coding ◽  
Video Codec ◽  
Available Bandwidth ◽  
Coding Efficiency ◽  
Cell Library ◽  
Processing Techniques

Extensive use of digital multimedia has led to the development of advance video processing techniques for development of multimedia applications. Application such as video surveillance requires 247 recording and streaming. So, the bandwidth and storage costs become significant. With introduction of video streaming over internet, where different kinds of end users request same content with different available bandwidth, it requires scalable video coding (SVC). These challenges can be overcome by developing new techniques to reduce redundancy in subsequent frames and to improve the coding efficiency. In this paper, overlapping weighted linear sum (OWLS) pre-processing method and its hardware architecture are proposed. It is implemented using field progrmmable gate array (FPGA) and the application specific integrated circuit (ASIC) is also developed using TSMC180nm technology standard cell library. Results show improvement in terms of power and area as compared to the existing work. In motion compensated temporal filtering (MCTF), wavelet transform is implemented by temporal filters. Architecture for 5/3 Lifting MCTF is also implemented and compared with baseline H.264 video codec. Simulation results show that the average peak signal to noise ratio (PSNR) improvement is 2.36[Formula: see text]dB. The MCTF design using 5/3 Lifting filter is synthesized for Virtex-5 FPGA and compared with the existing close-loop architecture with better performance.

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