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Short Project-Based Learning with MATLAB Applications to Support the Learning of video-image processing

JOURNAL OF SCIENCE EDUCATION AND TECHNOLOGY 2017年第5期26卷 508-518页

作者： Gil, Pablo Univ Alicante Dept Phys Syst Engn & Signal Theory Alicante 03690 Spain

University courses concerning Computer Vision and image processing are generally taught using a traditional methodology that is focused on the teacher rather than on the students. This approach is consequently not effective when teachers seek to attain cognitive objectives involving their students' critical thinking. This manuscript covers the development, implementation and assessment of a short project-based engineering course with MATLAB applications Multimedia Engineering being taken by Bachelor's degree students. The principal goal of all course lectures and hands-on laboratory activities was for the students to not only acquire image-specific technical skills but also a general knowledge of data analysis so as to locate phenomena in pixel regions of images and video frames. This would hopefully enable the students to develop skills regarding the implementation of the filters, operators, methods and techniques used for image processing and computer vision software libraries. Our teaching-learning process thus permits the accomplishment of knowledge assimilation, student motivation and skill development through the use of a continuous evaluation strategy to solve practical and real problems by means of short projects designed using MATLAB applications. Project-based learning is not new. This approach has been used in STEM learning in recent decades. But there are many types of projects. The aim of the current study is to analyse the efficacy of short projects as a learning tool when compared to long projects during which the students work with more independence. This work additionally presents the impact of different types of activities, and not only short projects, on students' overall results in this subject. Moreover, a statistical study has allowed the author to suggest a link between the students' success ratio and the type of content covered and activities completed on the course. The results described in this paper show that those students who took part i

关键词： Engineering education Project-based learning Educational technology system video and image processing

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Scalable and Resolution Data Analysis of image and video Compression using DL-CNNS Neural Network

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CIRCUITS SYSTEMS AND SIGNAL processing 2025年第3期44卷 1845-1864页

作者： Ajal, A. J. Karuppusamy, S. Anbu Excel Engn Coll Namakkal Tamilnadu India Excel Engn Coll Dept ECE Namakkal Tamilnadu India

images and videos processing are becoming more and more crucial in digital interactions. For those interactions, deep learning has had great success in processing them. High-quality image and video footage is difficult to receive, distribute, reveal and compress due to the vast volume and advancements in resolution. The primary goal of this research was to develop a CNN based on DL for video and image compression to achieve good scalability and resolution. In this study, CNN was used to remove duplicate frames, while GAN and LSTM were utilized to identify minute changes and repeat single images and videos during compression. The DL-based CNN model's output vector calculates the degree of similarity between frames. The training process is stabilized and discrepancies between the generator output and the training aim are reduced using GAN. Repeated experiments on a range of videos and images with different sizes, durations, and quality levels demonstrated a significant resampling rate. In the end, the suggested approach achieves a 3% gain in PSNR, a 4.5% increase in SSIM, and a 50% decrease in RD cost during a video compression experiment-a considerable improvement over the performance of the current versatile video coding (VVC) technique in terms of PSNR, SSIM, compression ratio, and RD cost. The results of the image compression experiment include standard color images for testing using SSIM values (0.78-98), NPCR during compression (92-98%), and PSNR for image resolution (42-43%). When comparing the final product to the source video and image, there was often a 10% variation in quality and a size difference of more than half. Therefore, the proposed approach outperforms current approaches in terms of cost and compression ratio, according to simulation findings.

关键词： Convolution Neural Networks Deep learning video and image processing Compression JPEG

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Attention to Emotions: Body Emotion Recognition In-the-Wild Using Self-attention Transformer Network 18th

Attention to Emotions: Body Emotion Recognition In-the-Wild ...

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18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP) / 18th International Conference on Computer Graphics Theory and Applications

作者： Paiva, Pedro V. V. Ramos, Josue J. G. Gavrilova, Marina Carvalho, Marco A. G. Univ Estadual Campinas Sch Technol Limeira Brazil Renato Archer IT Ctr Cyber Phys Syst Div Campinas Brazil Univ Calgary Dept Comp Sci Calgary AB Canada

ISBN: (纸本)9783031667428;9783031667435

Body movements are an essential part of non-verbal communication as they help to express and interpret human emotions. The potential of Body Emotion Recognition (BER) is immense, as it can provide insights into user preferences, automate real-time exchanges and enable machines to respond to human emotions. BER finds applications in customer service, healthcare, entertainment, emotion-aware robots, and other areas. While face expression-based techniques are extensively researched, detecting emotions from body movements in the realworld presents several challenges, including variations in body posture, occlusions, and background. Recent research has established the efficacy of transformer deep-learning models beyond the language domain to solve video and image-related problems. A key component of transformers is the self-attention mechanism, which captures relationships among features across different spatial locations, allowing contextual information extraction. In this study, we aim to understand the role of body movements in emotion expression and to explore the use of transformer networks for body emotion recognition. Our method proposes a novel linear projection function of the visual transformer, which enables the transformation of 2D joint coordinates into a conventional matrix representation. Using an original method of contextual information learning, the developed approach enables a more accurate recognition of emotions by establishing unique correlations between individual's body motions over time. Our results demonstrated that the self-attention mechanism was able to achieve high accuracy in predicting emotions from body movements, surpassing the performance of other recent deep-learning methods. In addition, the impact of dataset size and frame rate on classification performance is analyzed.

关键词： Body emotion recognition Affective computing video and image processing Gait analysis Attention-based design

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Self-modifiable image processing library for model-based design on FPGAs

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IEEE LATIN AMERICA TRANSACTIONS 2019年第5期17卷 742-750页

作者： Garces-Socarras, L. Cabrera, A. Sanchez-Solano, S. Brox, P. Ieno, E. Pimenta, T. Univ Tecnol La Habana Jose Antonio Echeverria CUJ Havana Cuba Univ Seville CSIC IMSE CNM Inst Microelectron Sevilla Seville Spain Ctr Fed Educ Tecnol Minas Gerais CEFET MG Varginha MG Brazil Univ Fed Itajuba UNIFEI Itajuba MG Brazil

This paper describes highly configurable hardware modules, included in XIL XSGImgLib library, capable of speed up the hardware implementation of video and image processing systems using the model-based design flow provided by Xilinx System Generator. As part of this work, generic architectures were developed to exploit specific characteristics of some processing blocks, which can be self-modified using a novel software procedure developed for MATLAB (R). This procedure, along with the generic architecture and the configuration options, allows the abstraction about the specific details of the hardware implementation, as well as the adjustment of the resources consumption of the high-speed image and video processing application for embedded systems with weight, volume and power consumption constrains like smart cameras, video surveillance and autonomous vehicles. The use of this video and image processing library is illustrated by the development of a segmentation application on a Spartan-6 LX45 FPGA although any Xilinx's FPGA is supported.

关键词： video and image processing XIL XSGImgLib FPGA Xilinx System Generator Model-based design flow MATLAB (R) Simulink (R)

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Efficient architecture for direct 8x8 2D DCTcomputations with earlier zigzag ordering

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MULTIMEDIA TOOLS AND APPLICATIONS 2016年第11期75卷 6121-6141页

作者： Hatim, Anas Belkouch, Said Benslimane, Abderrahim Hassani, Moha M'Rabet Sadiki, Tayeb Univ Cadi Ayyad Ecole Natl Sci Appl Embedded Syst & Digital Control Lab PB 575Av Abdelkarim Khattabi Marrakech Morocco Univ Avignon LIA CERI BP *** Avignon 9 France Cadi Ayyad Univ Fac Sci Semlalia Marrakech Morocco Int Univ Rabat UIR ELIT Dept Rabat Morocco

In this paper, we propose a low complexity architecture for direct 2D DCT zigzag reordering and quantization merged architecture. The architecture will transform the pixels from spatial to spectral domain with the required quality constraints of the compression standards. We developed a new architecture to achieve the computations of the 2D DCT directly without any transposition memory. The coefficients are quantized and approximated using shift operations. We defined Sk functions blocks to build the 2D DCT architecture. The Sk block performs 8 functions depending on the control signals of the system. The number of additions/subtractions used is 63. Moreover, no multiplications and no transposition memory are needed. The sequence of the 2D DCT coefficients is computed with respect to the zigzag reordering. This allows us to produce zigzag ordered 2D DCT coefficients. The architecture is suitable for usage with statistical rules to predict the zero quantized coefficients, which can considerably reduce the video processing computations. The architecture is easily extensible to increase its performances. We implemented the design using an FPGA Cyclone 3. The design can reach up to 244 MHz and uses 1188 logic elements, and respects the real time HDTV video requirements with low power consumption.

关键词： DCT Zigzag Quantification FPGA image compression video and image processing

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Embedded Computing Technology for Highly-demanding Cyber-physical Systems 13

Embedded Computing Technology for Highly-demanding Cyber-phy...

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13th IFAC and IEEE Conference on Programmable Devices and Embedded Systems

作者： Jozwiak, Lech Eindhoven Univ Technol NL-5600 MB Eindhoven Netherlands

The recent spectacular progress in the microelectronic, information, communication, material and sensor technologies created a big stimulus towards development of much more sophisticated, coherent and fit to use, smart communicating cyber-physical systems (CPS). The huge and rapidly developing markets of the modern CPS represent great opportunities for both private enterprises and country economies. However, these opportunities come with a price of unusual systems complexity. as well as, stringent and difficult to satisfy requirements of the modern CPS applications. Specifically, numerous mobile and autonomous CPS applications require a. o. a guaranteed (ultra-)high performance or (ultra-)low energy consumption, as well as, a high reliability, safety and security. To adequately address these problems and overcome the related challenges a sophisticated embedded computing and embedded design technologies are needed. After a brief introduction to modern CPS and consideration of several serious challenges of their design, this paper discusses the embedded computing technology needed for the modern complex and highly-demanding mobile and autonomous CPS. (C) 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. Ail rights reserved.

关键词： cyber-physical systems embedded processors application-specific processors multiprocessor system on a chip (MPSoC) mobile systems autonomous systems smart wearables smart cars video and image processing high performance low energy consumption

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A General-Purpose FPGA-Based Reconfigurable Platform for video and image processing

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6th International Symposium on Neural Networks

作者： Li, Jie He, Haibo Man, Hong Desai, Sachi Stevens Inst Technol Dept Elect & Comp Engn Hoboken NJ 07030 USA US Army ARDEC Picatinny Arsenal NJ 07806 USA

ISBN: (纸本)9783642015120

This paper presents a general-purpose, multi-task, and re-configurable platform for video and image processing. With the increasing requirements of processing power in many of today's video and image processing applications, it is important to go beyond the software implementation to provide a real-time, low cost, high performance, and scalable hardware platform. In this paper, we propose a system by using the powerful parallel processing architecture in the Field Programmable Gate Army (FPGA) to achieve this objective. Based on the proposed system level architecture and design strategies, a prototype system is developed based on the Xilinx Virtex-II FPGA with the integration of embedded processor, memory control and interface technologies. Our system includes different functional modules, such as edge detection, zoom-in and zoom-out functions which provides the flexibility of rising this system as a general video processing platform according to different application requirements. The final system utilize about 20% of logic resource, 50% of memory on chip, and has total power consumption around 203 mw.

关键词： Reconfigurable system FPGA design video and image processing edge detection image scaling

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Single-Phase Velocity Determination Based in video and Sub-images processing:An Optical Flow Method Implemented with Support of a Programmed MatLab Structured Script

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Journal of Software Engineering and Applications 2015年第6期8卷 290-294页

作者： Andreas Nascimento Edson Da Costa Bortoni José Luiz Goncalves Pedro Antunes Duarte Mauro Hugo Mathias Departamento de Mecanica Faculdade de EngenhariaCampus de Guaratinguetá(FEG)Universidade Estadual Paulista(UNESP)GuaratinguetáBrazil Universidade Federal de Itajubá(UNIFEI) ItajubáBrazil

Important in many different sectors of the industry, the determination of stream velocity has become more and more important due to measurements precision necessity, in order to determine the right production rates, determine the volumetric production of undesired fluid, establish automated controls based on these measurements avoiding over-flooding or over-production, guaranteeing accurate predictive maintenance, etc. Difficulties being faced have been the determination of the velocity of specific fluids embedded in some others, for example, determining the gas bubbles stream velocity flowing throughout liquid fluid phase. Although different and already applicable methods have been researched and already implemented within the industry, a non-intrusive automated way of providing those stream velocities has its importance, and may have a huge impact in projects budget. Knowing the importance of its determination, this developed script uses a methodology of breaking-down real-time videos media into frame images, analyzing by pixel correlations possible superposition matches for further gas bubbles stream velocity estimation. In raw sense, the script bases itself in functions and procedures already available in MatLab, which can be used for image processing and treatments, allowing the methodology to be implemented. Its accuracy after the running test was of around 97% (ninety-seven percent);the raw source code with comments had almost 3000 (three thousand) characters;and the hardware placed for running the code was an Intel Core Duo 2.13 [Ghz] and 2 [Gb] RAM memory capable workstation. Even showing good results, it could be stated that just the end point correlations were actually getting to the final solution. So that, making use of self-learning functions or neural network, one could surely enhance the capability of the application to be run in real-time without getting exhaust by iterative loops.

关键词： Optical Flow Single-Phase Velocity video and image processing Sensing MatLab Script

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Smart Traffic Lights Switching and Traffic Density Calculation using video processing

Smart Traffic Lights Switching and Traffic Density Calculati...

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Conference on Recent Advances in Engineering and Computational Sciences (RAECS)

作者： Kanungo, Anurag Sharma, Ayush Singla, Chetan Panjab Univ Univ Inst Engn & Technol Chandigarh 160014 India

ISBN: (纸本)9781479922918

Congestion in traffic is a serious problem nowadays. Although it seems to pervade everywhere, mega cities are the ones most affected by it. And it's ever increasing nature makes it imperative to know the road traffic density in real time for better signal control and effective traffic management. There can be different causes of congestion in traffic like insufficient capacity, unrestrained demand, large Red Light delays etc. While insufficient capacity and unrestrained demand are somewhere interrelated, the delay of respective light is hard coded and not dependent on traffic. Therefore the need for simulating and optimizing traffic control to better accommodate this increasing demand arises. In recent years, video monitoring and surveillance systems have been widely used in traffic management for traveler's information, ramp metering and updates in real time. The traffic density estimation and vehicle classification can also be achieved using video monitoring systems. This paper presents the method to use live video feed from the cameras at traffic junctions for real time traffic density calculation using video and image processing. It also focuses on the algorithm for switching the traffic lights according to vehicle density on road, thereby aiming at reducing the traffic congestion on roads which will help lower the number of accidents. In turn it will provide safe transit to people and reduce fuel consumption and waiting time. It will also provide significant data which will help in future road planning and analysis. In further stages multiple traffic lights can be synchronized with each other with an aim of even less traffic congestion and free flow of traffic.

关键词： Hardcoded versus intelligent traffic control Junction Traffic Simulation Reduced Traffic Congestion Signal Control Switching Algorithm Traffic Density Calculation video and image processing

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A vision-based system for early fire detection

A vision-based system for early fire detection

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IEEE International Conference on Systems, Man, and Cybernetics (SMC)

作者： Santana, Pedro Gomes, Pedro Barata, Jose Univ Nova Lisboa CTS UNINOVA Lisbon Portugal

ISBN: (纸本)9781467317146

This paper presents a video-based early fire detection system. Focus is given to the challenges related to the actual deployment of the vision system. Most importantly, background subtraction is performed in a windowed way for improved accuracy, an attentive mechanism is employed to focus a computationally expensive frequency analysis of potential fire regions, interaction with a people detection and tracking system is included so as to enable model-based false alarms rejection, a new colour-based model of fire's appearance as well as a new Wavelet-based model of fire's frequency signature are proposed, and the camera-world mapping is approximated according to a GPS-based learning calibration process. An average success rate of 92.7% at a processing rate of 10 Hz shows the applicability of the model to real-life applications.

关键词： Fire detection video and image processing computer vision systems

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