The document discusses algorithms for resizing digital videos. It describes scaling and cropping as basic resizing techniques that do not consider content. Seam carving is introduced as a better approach, removing seams or paths of pixels based on an "energy function" of importance. For video, seam carving is applied across frames as connected seam surfaces rather than individually, but computation takes considerable time. The goal is to remove unimportant content when adapting videos to different devices and aspect ratios.
This document contains a lecture on image compression. It begins with definitions of image compression and discusses the goals of data reduction and retaining necessary visual information. It describes different types of redundancy in images like coding, inter-pixel, and psychovisual redundancy that compression algorithms exploit. Common lossy and lossless compression techniques are outlined like Run Length Encoding, Huffman coding, and JPEG. The document emphasizes that compression is an application-specific balance between file size reduction and maintaining enough visual quality.
This document provides an introduction to the Introduction to Computer Graphics course ITCS 4120/5120 at UNCC. It outlines the prerequisites, tools used, and an overview of the course content which includes the history and applications of computer graphics, core disciplines, image synthesis processes, coordinate systems, image data structures, and basic display hardware. The course focuses on algorithms, mathematics, and programming projects in C++ and OpenGL.
This is the basic introductory presentation for beginners. It gives you the idea about what is image processing means. The presentation consists of introduction to digital image processing, image enhancement, image filtering, finding an image edge, image analysis, tools for image processing and finally some application of digital image processing.
Cobecho SL is an advertising agency located in Pontevedra, Galicia, Spain that offers competitive pricing and discounts for new clients. It prides itself on being a creative laboratory that provides solutions beyond traditional advertising for its big clients. The agency can be found at 102 Avenida Castelao in Illa de Arousa, Pontevedra, Galicia, Spain.
There are over 100,000 engineering materials to choose from. The typical design engineer should have ready access to information on 30 to 60 materials, depending on the range of applications he or she deals with.
An Approach for Image Deblurring: Based on Sparse Representation and Regulari...IRJET Journal
This document proposes an approach for image deblurring based on sparse representation and a regularized filter. The approach splits the blurred input image into patches, estimates sparse coefficients for each patch using dictionary learning, updates the dictionary, and estimates the deblur kernel. The deblur kernel is applied using Wiener deconvolution and further processed with a regularized filter to recover the original image. The approach was tested on MATLAB and evaluation metrics like RMSE, PSNR, and SSIM along with visual analysis showed it performed better deblurring compared to existing methods.
Practical and Robust Stenciled Shadow Volumes for Hardware-Accelerated RenderingMark Kilgard
Twenty-five years ago, Crow published the shadow volume approach for determining shadowed regions in a scene. A decade ago, Heidmann described a hardware-accelerated stencil bufferbased shadow volume algorithm. However, hardware-accelerated stenciled shadow volume techniques have not been widely adopted by 3D games and applications due in large part to the lack of robustness of described techniques. This situation persists despite widely available hardware support. Specifically what has been lacking is a technique that robustly handles various "hard" situations created by near or far plane clipping of shadow volumes. We describe a robust, artifact-free technique for hardwareaccelerated rendering of stenciled shadow volumes. Assuming existing hardware, we resolve the issues otherwise caused by shadow volume near and far plane clipping through a combination of (1) placing the conventional far clip plane “at infinity”, (2) rasterization with infinite shadow volume polygons via homogeneous coordinates, and (3) adopting a zfail stencil-testing scheme. Depth clamping, a new rasterization feature provided by NVIDIA's GeForce3 & GeForce4 Ti GPUs, preserves existing depth precision by not requiring the far plane to be placed at infinity. We also propose two-sided stencil testing to improve the efficiency of rendering stenciled shadow volumes.
March 12, 2002.
This was submitted to the SIGGRAPH 2002 papers committee but was rejected.
This document provides an overview of convolutional neural networks (CNNs or ConvNets). It discusses the history of ConvNets from their origins in modeling the visual cortex to modern applications in computer vision tasks. The document explains what ConvNets are through their use of filters, activation maps, and pooling layers. It also discusses methods for visualizing and understanding what different layers of ConvNets are learning from images.
This document contains a lecture on image compression. It begins with definitions of image compression and discusses the goals of data reduction and retaining necessary visual information. It describes different types of redundancy in images like coding, inter-pixel, and psychovisual redundancy that compression algorithms exploit. Common lossy and lossless compression techniques are outlined like Run Length Encoding, Huffman coding, and JPEG. The document emphasizes that compression is an application-specific balance between file size reduction and maintaining enough visual quality.
This document provides an introduction to the Introduction to Computer Graphics course ITCS 4120/5120 at UNCC. It outlines the prerequisites, tools used, and an overview of the course content which includes the history and applications of computer graphics, core disciplines, image synthesis processes, coordinate systems, image data structures, and basic display hardware. The course focuses on algorithms, mathematics, and programming projects in C++ and OpenGL.
This is the basic introductory presentation for beginners. It gives you the idea about what is image processing means. The presentation consists of introduction to digital image processing, image enhancement, image filtering, finding an image edge, image analysis, tools for image processing and finally some application of digital image processing.
Cobecho SL is an advertising agency located in Pontevedra, Galicia, Spain that offers competitive pricing and discounts for new clients. It prides itself on being a creative laboratory that provides solutions beyond traditional advertising for its big clients. The agency can be found at 102 Avenida Castelao in Illa de Arousa, Pontevedra, Galicia, Spain.
There are over 100,000 engineering materials to choose from. The typical design engineer should have ready access to information on 30 to 60 materials, depending on the range of applications he or she deals with.
An Approach for Image Deblurring: Based on Sparse Representation and Regulari...IRJET Journal
This document proposes an approach for image deblurring based on sparse representation and a regularized filter. The approach splits the blurred input image into patches, estimates sparse coefficients for each patch using dictionary learning, updates the dictionary, and estimates the deblur kernel. The deblur kernel is applied using Wiener deconvolution and further processed with a regularized filter to recover the original image. The approach was tested on MATLAB and evaluation metrics like RMSE, PSNR, and SSIM along with visual analysis showed it performed better deblurring compared to existing methods.
Practical and Robust Stenciled Shadow Volumes for Hardware-Accelerated RenderingMark Kilgard
Twenty-five years ago, Crow published the shadow volume approach for determining shadowed regions in a scene. A decade ago, Heidmann described a hardware-accelerated stencil bufferbased shadow volume algorithm. However, hardware-accelerated stenciled shadow volume techniques have not been widely adopted by 3D games and applications due in large part to the lack of robustness of described techniques. This situation persists despite widely available hardware support. Specifically what has been lacking is a technique that robustly handles various "hard" situations created by near or far plane clipping of shadow volumes. We describe a robust, artifact-free technique for hardwareaccelerated rendering of stenciled shadow volumes. Assuming existing hardware, we resolve the issues otherwise caused by shadow volume near and far plane clipping through a combination of (1) placing the conventional far clip plane “at infinity”, (2) rasterization with infinite shadow volume polygons via homogeneous coordinates, and (3) adopting a zfail stencil-testing scheme. Depth clamping, a new rasterization feature provided by NVIDIA's GeForce3 & GeForce4 Ti GPUs, preserves existing depth precision by not requiring the far plane to be placed at infinity. We also propose two-sided stencil testing to improve the efficiency of rendering stenciled shadow volumes.
March 12, 2002.
This was submitted to the SIGGRAPH 2002 papers committee but was rejected.
This document provides an overview of convolutional neural networks (CNNs or ConvNets). It discusses the history of ConvNets from their origins in modeling the visual cortex to modern applications in computer vision tasks. The document explains what ConvNets are through their use of filters, activation maps, and pooling layers. It also discusses methods for visualizing and understanding what different layers of ConvNets are learning from images.
A recent direction in Business Process Management studied methodologies to control the execution of Business Processes under several sources of uncertainty in order to always get to the end by satisfying all constraints. Current approaches encode business processes into temporal constraint networks or timed game automata in order to exploit their related strategy synthesis algorithms. However, the proposed encodings can only synthesize single-strategies and fail to handle loops. To overcome these limits I will discuss a recent approach based on supervisory control. The approach considers structured business processes with resources, parallel and mutually exclusive branches, loops, and uncertainty. I will discuss an encoding into finite state automata and prove that their concurrent behavior models exactly all possible executions of the process. After that, I will introduce tentative commitment constraints as a new class of constraints restricting the executions of a process. Finally, I will discuss a tree decomposition of the process that plays a central role in modular supervisory control.
In his ignite talk „The Digital Transformation of Education: A Hyper-Disruptive Era through Blockchain and Generative AI,“ Dr. Alexander Pfeiffer delves into the intricate challenges and potential benefits associated with integrating blockchain technologies and generative AI into the educational landscape. He scrutinizes consensus algorithms and explores sustainable methods of operating blockchain systems, while also examining how smart contracts and transactions can be tailored to meet the specific needs of the educational sector. Alexander underscores the importance of establishing secure digital identities and ensuring robust data protection, while simultaneously casting a critical eye on potential risks and vulnerabilities. The topic of digital identities, facilitated through tokenization, forms a bridge between storing data using blockchain-based databases and the increasingly urgent need for content verification of AI-generated material.
Alexander explores the profound alterations occurring in teaching methodologies, assignment creation, and evaluation processes, shedding light on the hyper-disruptive impact these changes are having on both research and practical applications in education. The production of textual content by educators and students is analyzed with a focus on ensuring clear traceability of content sources and editors, and its proper citation, a critical aspect in the responsible use of AI. In addition to generative text and graphics, AI plays a crucial role in future learning and assignment practices, particularly through adaptive game-based learning and assessment. Alexander will provide a brief glimpse into his game „Gallery-Defender,“ a prototype demonstrating how AI and blockchain can be effectively implemented in serious gaming scenarios.
Furthermore, he emphasizes the imperative for ongoing education and professional development for educational personnel, advocating for a proactive stance in addressing the (legal) challenges associated with AI-generated images and text. This ignite talk aims to provide a balanced and critically reflective perspective on hyper-disruptive technologies, setting the stage for further discourse and exploration in the subsequent discussion.
The simulation of melee combat is central to many contemporary and traditional strategic games and simulations. In order to elevate this element of play from mere exercises of stats-comparison and dice rolling to a meaningful experience of play, strategy games rely on a rich plethora of cultural motives as deciding factors of their mechanic design. On the example of Samurai-themed skirmishing games, my talk elaborates on the impact that (popular) culture and other inspirations have on gaming experiences. It provides concrete examples from Japanese history, its traditional cinema, and postmodern Western reflections of Japanese cultural practices. Based on these insights, it compares four tabletop strategy games, muses on which phenomena they have adapted in their mechanics, and asks why or why not they may succeed in capturing a cultural essence via their rules.
Ultimately, this comparative approach shall serve to decipher the interplay of dice mechanics and aesthetic properties as the longing for a dramatic ideal in tabletop gaming and encourage participants to reflect on the idea in a subsequent, shared gaming experience.
How does a development team expand on an already existing game?
We will look at the two community driven and committee led expansions to the abandoned Tabletop game 'GuildBall' and explore the stages of development that the game went through. The art and lore driven approach employed will show us how rough sketches and concept ideas become a fully fledged ruleset and ultimately miniatures that can be put on the table. We will also explore pitfalls in rules design like over complicating abilities, the lack of streamlining across the game or simply creating expansions who break the game instead of the mold.
The document discusses Ben Calvert-Lee's work developing miniatures for tabletop games. It begins with an introduction to Ben's background and current role as a freelance lead sculptor. It then outlines the typical development pipeline for miniatures, from initial concepts and artwork to production. The document also discusses different miniature production methods. A case study details Ben's process for developing the Tengu faction for a game, including exploring species archetypes and incorporating unexpected developments into the designs.
In recent years, we have experienced an exponential growth in the amount of data generated by IoT devices. Data have to be processed strict low latency constraints, that cannot be addressed by conventional computing paradigm and architectures. On top of this, if we consider that we recently hit the limit codified by the Moore’s law, satisfying low-latency requirements of modern applications will become even more challenging in the future. In this talk, we discuss challenges and possibilities of heterogeneous distributed systems in the Post-Moore era.
In the modern world, we are permanently using, leveraging, interacting with, and relying upon systems of ever higher sophistication, ranging from our cars, recommender systems in eCommerce, and networks when we go online, to integrated circuits when using our PCs and smartphones, security-critical software when accessing our bank accounts, and spreadsheets for financial planning and decision making. The complexity of these systems coupled with our high dependency on them implies both a non-negligible likelihood of system failures, and a high potential that such failures have significant negative effects on our everyday life. For that reason, it is a vital requirement to keep the harm of emerging failures to a minimum, which means minimizing the system downtime as well as the cost of system repair. This is where model-based diagnosis comes into play.
Model-based diagnosis is a principled, domain-independent approach that can be generally applied to troubleshoot systems of a wide variety of types, including all the ones mentioned above. It exploits and orchestrates techniques for knowledge representation, automated reasoning, heuristic problem solving, intelligent search, learning, stochastics, statistics, decision making under uncertainty, as well as combinatorics and set theory to detect, localize, and fix faults in abnormally behaving systems.
In this talk, we will give an introduction to the topic of model-based diagnosis, point out the major challenges in the field, and discuss a selection of approaches from our research addressing these challenges. For instance, we will present methods for the optimization of the time and memory performance of diagnosis systems, show efficient techniques for a semi-automatic debugging by interacting with a user or expert, and demonstrate how our algorithms can be effectively leveraged in important application domains such as scheduling or the Semantic Web.
Function-as-a-Service (FaaS) is the latest paradigm of cloud computing in which developers deploy their codes as serverless functions, while the entire underlying platform and infrastructure is completely managed by cloud providers. Each cloud provider offers a huge set of cloud services and many libraries to simplify development and deployment, but only inside their clouds, often in a single cloud region. With such „help“ of cloud providers, users are locked to use resources and services of the selected cloud provider, which are often limited. Moreover, such heterogeneous and distributed environment of multiple cloud regions and providers challenge scientists to engineer cloud applications, often in a form of serverless workflows. In this talk, I will present our design principle „code once, run everywhere, with everything“. In particular, I will present challenges and our approaches and techniques how to program, model, orchestrate, and run distributed serverless workflow applications in federated FaaS.
This document summarizes a presentation on machine learning and fluid network planes. It begins with an agenda and introduction to fluid network planes and instances. It then discusses the role of machine learning in fluid network planes, including applications such as optimization, virtual network embedding problems, run-time operations, and intent-based closed-loop automation. Recent research is presented on machine learning-based YouTube QoE estimation using real 4G/5G network traces to predict video quality and inform control actions. Results are shown comparing 4G and 5G networks in terms of radio parameters, stalling events, handovers, and video resolutions under different mobility conditions.
The dynamics of networks enables the function of a variety of systems we rely on every day, from gene regulation and metabolism in the cell to the distribution of electric power and communication of information. Understanding, steering and predicting the function of interacting nonlinear dynamical systems, in particular if they are externally driven out of equilibrium, relies on obtaining and evaluating suitable models, posing at least two major challenges. First, how can we extract key structural system features of networks if only time series data provide information about the dynamics of (some) units? Second, how can we characterize nonlinear responses of nonlinear multi-dimensional systems externally driven by fluctuations, and consequently, predict tipping points at which normal operational states may be lost? Here we report recent progress on nonlinear response theory extended to predict tipping points and on model-free inference of network structural features from observed dynamics.
When it comes to integrating digital technologies into the classroom in higher education, many teachers face similar challenges. Nevertheless, it is difficult for teachers to share experiences because it is usually not possible to transfer successful teaching scenarios directly from one area to another, as subject-specific characteristics make it difficult to reuse them. To address this problem, instructional scenarios can be described as patterns that have been used previously in educational contexts. Patterns can capture proven teaching strategies and describe instructional scenarios in a consistent structure that can be reused. Because priorities for content, methods, and tools are different in each domain, a consensus-tested taxonomy was first developed with the goal of modeling a domain-independent database to collect digital instructional practices. In addition, this presentation will present preliminary insights into a data-driven approach to identifying effective instructional practices from interdisciplinary data as patterns. A web-based application will be developed for this that can both collect teaching/learning scenarios and individually extract scenarios from patterns for a learning platform.
The document discusses performance characterization across a computing continuum from the edge to the cloud. It evaluates the performance of video encoding and machine learning tasks on different devices. For video encoding, older single-board computers had significantly higher encoding times than other resources but provided lower data transfer times. For machine learning, training a convolutional neural network took much longer than a simpler model. Cloud and fog resources generally outperformed edge devices for more complex tasks. The document recommends offloading large or complex tasks to more powerful resources when possible.
East-west oriented photovoltaic power system is a new trend in orienting photovoltaic system. This lecture presents an evaluation of east–west oriented photovoltaic power system. A comparison between east–west oriented photovoltaic system and south oriented photovoltaic system in terms of cost of energy and technical requirement is conducted is presented in this lecture. In addition to that, the benefits of using east–west oriented photovoltaic system are discussed in this paper.
The document discusses using randomized recurrent neural networks and signature-based methods for machine learning in finance. It proposes splitting the input-output map of a dynamical system into a "reservoir" part and a linear "readout" part. The signature of the input signal provides a natural candidate for the reservoir, as it is point-separating and linear functions on the signature can approximate continuous functionals via the universal approximation theorem. The goal of the talk is to prove how dynamical systems can be approximated using randomized recurrent networks, with precise convergence rates, and to view randomized deep networks through this lens.
We live in a “digital” world, the separation between physical and virtual makes (almost) no sense anymore. Here, the Corona pandemic has also acted as an accelerator/magnifier demonstrating that the future of our digital society is here with all its possibilities, but also shortcomings.
In his talk, Hannes Werthner will briefly reflect on the history of computer science, and then discuss the need for an interdisciplinary response to these shortcomings. Such an answer is the Digital Humanism, which looks at this interplay of technology and humankind, it analyzes, and, most importantly, tries to influence the complex interplay of technology and humankind, for a better society and life. In the second part he will discuss this approach, and show what was achieved since its first workshop in 2019, and what lies ahead.
In the latest years, we have witnessed a growing number of media transmitted and stored on computers and mobile devices. For this reason, there is an actual need to employ smart compression algorithms to reduce the size of our media files. However, such techniques are often responsible for severe reduction of user perceived quality. In this talk we present several approaches we have developed to restore degraded images and videos to match their original quality, making use of Generative Adversarial Networks. The aim of the talk is to highlight the main features of our research work, including the advantages of our solution, the current challenges and the possible directions for future improvements.
Recommendation systems today are widely used across many applications such as in multimedia content platforms, social networks, and ecommerce, to provide suggestions to users that are most likely to fulfill their needs, thereby improving the user experience. Academic research, to date, largely focuses on the performance of recommendation models in terms of ranking quality or accuracy measures, which often don’t directly translate into improvements in the real-world. In this talk, we present some of the most interesting challenges that we face in the personalization efforts at Netflix. The goal of this talk is to sunshine challenging research problems in industrial recommendation systems and start a conversation about exciting areas of future research.
The document discusses the evolution to 5G networks and their benefits. It covers 5G principles like enhanced mobile broadband, massive machine-type communication, and ultra-reliable low-latency communications. Statistics are provided on 5G subscriptions, deployments, and expected growth in mobile data traffic. Use cases like smart cities, VR/AR, and autonomous vehicles are described. The presentation outlines Ericsson's 5G experience and global footprint.
A recent direction in Business Process Management studied methodologies to control the execution of Business Processes under several sources of uncertainty in order to always get to the end by satisfying all constraints. Current approaches encode business processes into temporal constraint networks or timed game automata in order to exploit their related strategy synthesis algorithms. However, the proposed encodings can only synthesize single-strategies and fail to handle loops. To overcome these limits I will discuss a recent approach based on supervisory control. The approach considers structured business processes with resources, parallel and mutually exclusive branches, loops, and uncertainty. I will discuss an encoding into finite state automata and prove that their concurrent behavior models exactly all possible executions of the process. After that, I will introduce tentative commitment constraints as a new class of constraints restricting the executions of a process. Finally, I will discuss a tree decomposition of the process that plays a central role in modular supervisory control.
In his ignite talk „The Digital Transformation of Education: A Hyper-Disruptive Era through Blockchain and Generative AI,“ Dr. Alexander Pfeiffer delves into the intricate challenges and potential benefits associated with integrating blockchain technologies and generative AI into the educational landscape. He scrutinizes consensus algorithms and explores sustainable methods of operating blockchain systems, while also examining how smart contracts and transactions can be tailored to meet the specific needs of the educational sector. Alexander underscores the importance of establishing secure digital identities and ensuring robust data protection, while simultaneously casting a critical eye on potential risks and vulnerabilities. The topic of digital identities, facilitated through tokenization, forms a bridge between storing data using blockchain-based databases and the increasingly urgent need for content verification of AI-generated material.
Alexander explores the profound alterations occurring in teaching methodologies, assignment creation, and evaluation processes, shedding light on the hyper-disruptive impact these changes are having on both research and practical applications in education. The production of textual content by educators and students is analyzed with a focus on ensuring clear traceability of content sources and editors, and its proper citation, a critical aspect in the responsible use of AI. In addition to generative text and graphics, AI plays a crucial role in future learning and assignment practices, particularly through adaptive game-based learning and assessment. Alexander will provide a brief glimpse into his game „Gallery-Defender,“ a prototype demonstrating how AI and blockchain can be effectively implemented in serious gaming scenarios.
Furthermore, he emphasizes the imperative for ongoing education and professional development for educational personnel, advocating for a proactive stance in addressing the (legal) challenges associated with AI-generated images and text. This ignite talk aims to provide a balanced and critically reflective perspective on hyper-disruptive technologies, setting the stage for further discourse and exploration in the subsequent discussion.
The simulation of melee combat is central to many contemporary and traditional strategic games and simulations. In order to elevate this element of play from mere exercises of stats-comparison and dice rolling to a meaningful experience of play, strategy games rely on a rich plethora of cultural motives as deciding factors of their mechanic design. On the example of Samurai-themed skirmishing games, my talk elaborates on the impact that (popular) culture and other inspirations have on gaming experiences. It provides concrete examples from Japanese history, its traditional cinema, and postmodern Western reflections of Japanese cultural practices. Based on these insights, it compares four tabletop strategy games, muses on which phenomena they have adapted in their mechanics, and asks why or why not they may succeed in capturing a cultural essence via their rules.
Ultimately, this comparative approach shall serve to decipher the interplay of dice mechanics and aesthetic properties as the longing for a dramatic ideal in tabletop gaming and encourage participants to reflect on the idea in a subsequent, shared gaming experience.
How does a development team expand on an already existing game?
We will look at the two community driven and committee led expansions to the abandoned Tabletop game 'GuildBall' and explore the stages of development that the game went through. The art and lore driven approach employed will show us how rough sketches and concept ideas become a fully fledged ruleset and ultimately miniatures that can be put on the table. We will also explore pitfalls in rules design like over complicating abilities, the lack of streamlining across the game or simply creating expansions who break the game instead of the mold.
The document discusses Ben Calvert-Lee's work developing miniatures for tabletop games. It begins with an introduction to Ben's background and current role as a freelance lead sculptor. It then outlines the typical development pipeline for miniatures, from initial concepts and artwork to production. The document also discusses different miniature production methods. A case study details Ben's process for developing the Tengu faction for a game, including exploring species archetypes and incorporating unexpected developments into the designs.
In recent years, we have experienced an exponential growth in the amount of data generated by IoT devices. Data have to be processed strict low latency constraints, that cannot be addressed by conventional computing paradigm and architectures. On top of this, if we consider that we recently hit the limit codified by the Moore’s law, satisfying low-latency requirements of modern applications will become even more challenging in the future. In this talk, we discuss challenges and possibilities of heterogeneous distributed systems in the Post-Moore era.
In the modern world, we are permanently using, leveraging, interacting with, and relying upon systems of ever higher sophistication, ranging from our cars, recommender systems in eCommerce, and networks when we go online, to integrated circuits when using our PCs and smartphones, security-critical software when accessing our bank accounts, and spreadsheets for financial planning and decision making. The complexity of these systems coupled with our high dependency on them implies both a non-negligible likelihood of system failures, and a high potential that such failures have significant negative effects on our everyday life. For that reason, it is a vital requirement to keep the harm of emerging failures to a minimum, which means minimizing the system downtime as well as the cost of system repair. This is where model-based diagnosis comes into play.
Model-based diagnosis is a principled, domain-independent approach that can be generally applied to troubleshoot systems of a wide variety of types, including all the ones mentioned above. It exploits and orchestrates techniques for knowledge representation, automated reasoning, heuristic problem solving, intelligent search, learning, stochastics, statistics, decision making under uncertainty, as well as combinatorics and set theory to detect, localize, and fix faults in abnormally behaving systems.
In this talk, we will give an introduction to the topic of model-based diagnosis, point out the major challenges in the field, and discuss a selection of approaches from our research addressing these challenges. For instance, we will present methods for the optimization of the time and memory performance of diagnosis systems, show efficient techniques for a semi-automatic debugging by interacting with a user or expert, and demonstrate how our algorithms can be effectively leveraged in important application domains such as scheduling or the Semantic Web.
Function-as-a-Service (FaaS) is the latest paradigm of cloud computing in which developers deploy their codes as serverless functions, while the entire underlying platform and infrastructure is completely managed by cloud providers. Each cloud provider offers a huge set of cloud services and many libraries to simplify development and deployment, but only inside their clouds, often in a single cloud region. With such „help“ of cloud providers, users are locked to use resources and services of the selected cloud provider, which are often limited. Moreover, such heterogeneous and distributed environment of multiple cloud regions and providers challenge scientists to engineer cloud applications, often in a form of serverless workflows. In this talk, I will present our design principle „code once, run everywhere, with everything“. In particular, I will present challenges and our approaches and techniques how to program, model, orchestrate, and run distributed serverless workflow applications in federated FaaS.
This document summarizes a presentation on machine learning and fluid network planes. It begins with an agenda and introduction to fluid network planes and instances. It then discusses the role of machine learning in fluid network planes, including applications such as optimization, virtual network embedding problems, run-time operations, and intent-based closed-loop automation. Recent research is presented on machine learning-based YouTube QoE estimation using real 4G/5G network traces to predict video quality and inform control actions. Results are shown comparing 4G and 5G networks in terms of radio parameters, stalling events, handovers, and video resolutions under different mobility conditions.
The dynamics of networks enables the function of a variety of systems we rely on every day, from gene regulation and metabolism in the cell to the distribution of electric power and communication of information. Understanding, steering and predicting the function of interacting nonlinear dynamical systems, in particular if they are externally driven out of equilibrium, relies on obtaining and evaluating suitable models, posing at least two major challenges. First, how can we extract key structural system features of networks if only time series data provide information about the dynamics of (some) units? Second, how can we characterize nonlinear responses of nonlinear multi-dimensional systems externally driven by fluctuations, and consequently, predict tipping points at which normal operational states may be lost? Here we report recent progress on nonlinear response theory extended to predict tipping points and on model-free inference of network structural features from observed dynamics.
When it comes to integrating digital technologies into the classroom in higher education, many teachers face similar challenges. Nevertheless, it is difficult for teachers to share experiences because it is usually not possible to transfer successful teaching scenarios directly from one area to another, as subject-specific characteristics make it difficult to reuse them. To address this problem, instructional scenarios can be described as patterns that have been used previously in educational contexts. Patterns can capture proven teaching strategies and describe instructional scenarios in a consistent structure that can be reused. Because priorities for content, methods, and tools are different in each domain, a consensus-tested taxonomy was first developed with the goal of modeling a domain-independent database to collect digital instructional practices. In addition, this presentation will present preliminary insights into a data-driven approach to identifying effective instructional practices from interdisciplinary data as patterns. A web-based application will be developed for this that can both collect teaching/learning scenarios and individually extract scenarios from patterns for a learning platform.
The document discusses performance characterization across a computing continuum from the edge to the cloud. It evaluates the performance of video encoding and machine learning tasks on different devices. For video encoding, older single-board computers had significantly higher encoding times than other resources but provided lower data transfer times. For machine learning, training a convolutional neural network took much longer than a simpler model. Cloud and fog resources generally outperformed edge devices for more complex tasks. The document recommends offloading large or complex tasks to more powerful resources when possible.
East-west oriented photovoltaic power system is a new trend in orienting photovoltaic system. This lecture presents an evaluation of east–west oriented photovoltaic power system. A comparison between east–west oriented photovoltaic system and south oriented photovoltaic system in terms of cost of energy and technical requirement is conducted is presented in this lecture. In addition to that, the benefits of using east–west oriented photovoltaic system are discussed in this paper.
The document discusses using randomized recurrent neural networks and signature-based methods for machine learning in finance. It proposes splitting the input-output map of a dynamical system into a "reservoir" part and a linear "readout" part. The signature of the input signal provides a natural candidate for the reservoir, as it is point-separating and linear functions on the signature can approximate continuous functionals via the universal approximation theorem. The goal of the talk is to prove how dynamical systems can be approximated using randomized recurrent networks, with precise convergence rates, and to view randomized deep networks through this lens.
We live in a “digital” world, the separation between physical and virtual makes (almost) no sense anymore. Here, the Corona pandemic has also acted as an accelerator/magnifier demonstrating that the future of our digital society is here with all its possibilities, but also shortcomings.
In his talk, Hannes Werthner will briefly reflect on the history of computer science, and then discuss the need for an interdisciplinary response to these shortcomings. Such an answer is the Digital Humanism, which looks at this interplay of technology and humankind, it analyzes, and, most importantly, tries to influence the complex interplay of technology and humankind, for a better society and life. In the second part he will discuss this approach, and show what was achieved since its first workshop in 2019, and what lies ahead.
In the latest years, we have witnessed a growing number of media transmitted and stored on computers and mobile devices. For this reason, there is an actual need to employ smart compression algorithms to reduce the size of our media files. However, such techniques are often responsible for severe reduction of user perceived quality. In this talk we present several approaches we have developed to restore degraded images and videos to match their original quality, making use of Generative Adversarial Networks. The aim of the talk is to highlight the main features of our research work, including the advantages of our solution, the current challenges and the possible directions for future improvements.
Recommendation systems today are widely used across many applications such as in multimedia content platforms, social networks, and ecommerce, to provide suggestions to users that are most likely to fulfill their needs, thereby improving the user experience. Academic research, to date, largely focuses on the performance of recommendation models in terms of ranking quality or accuracy measures, which often don’t directly translate into improvements in the real-world. In this talk, we present some of the most interesting challenges that we face in the personalization efforts at Netflix. The goal of this talk is to sunshine challenging research problems in industrial recommendation systems and start a conversation about exciting areas of future research.
The document discusses the evolution to 5G networks and their benefits. It covers 5G principles like enhanced mobile broadband, massive machine-type communication, and ultra-reliable low-latency communications. Statistics are provided on 5G subscriptions, deployments, and expected growth in mobile data traffic. Use cases like smart cities, VR/AR, and autonomous vehicles are described. The presentation outlines Ericsson's 5G experience and global footprint.
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/how-axelera-ai-uses-digital-compute-in-memory-to-deliver-fast-and-energy-efficient-computer-vision-a-presentation-from-axelera-ai/
Bram Verhoef, Head of Machine Learning at Axelera AI, presents the “How Axelera AI Uses Digital Compute-in-memory to Deliver Fast and Energy-efficient Computer Vision” tutorial at the May 2024 Embedded Vision Summit.
As artificial intelligence inference transitions from cloud environments to edge locations, computer vision applications achieve heightened responsiveness, reliability and privacy. This migration, however, introduces the challenge of operating within the stringent confines of resource constraints typical at the edge, including small form factors, low energy budgets and diminished memory and computational capacities. Axelera AI addresses these challenges through an innovative approach of performing digital computations within memory itself. This technique facilitates the realization of high-performance, energy-efficient and cost-effective computer vision capabilities at the thin and thick edge, extending the frontier of what is achievable with current technologies.
In this presentation, Verhoef unveils his company’s pioneering chip technology and demonstrates its capacity to deliver exceptional frames-per-second performance across a range of standard computer vision networks typical of applications in security, surveillance and the industrial sector. This shows that advanced computer vision can be accessible and efficient, even at the very edge of our technological ecosystem.
Digital Banking in the Cloud: How Citizens Bank Unlocked Their MainframePrecisely
Inconsistent user experience and siloed data, high costs, and changing customer expectations – Citizens Bank was experiencing these challenges while it was attempting to deliver a superior digital banking experience for its clients. Its core banking applications run on the mainframe and Citizens was using legacy utilities to get the critical mainframe data to feed customer-facing channels, like call centers, web, and mobile. Ultimately, this led to higher operating costs (MIPS), delayed response times, and longer time to market.
Ever-changing customer expectations demand more modern digital experiences, and the bank needed to find a solution that could provide real-time data to its customer channels with low latency and operating costs. Join this session to learn how Citizens is leveraging Precisely to replicate mainframe data to its customer channels and deliver on their “modern digital bank” experiences.
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
Northern Engraving | Nameplate Manufacturing Process - 2024Northern Engraving
Manufacturing custom quality metal nameplates and badges involves several standard operations. Processes include sheet prep, lithography, screening, coating, punch press and inspection. All decoration is completed in the flat sheet with adhesive and tooling operations following. The possibilities for creating unique durable nameplates are endless. How will you create your brand identity? We can help!
zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...Alex Pruden
Folding is a recent technique for building efficient recursive SNARKs. Several elegant folding protocols have been proposed, such as Nova, Supernova, Hypernova, Protostar, and others. However, all of them rely on an additively homomorphic commitment scheme based on discrete log, and are therefore not post-quantum secure. In this work we present LatticeFold, the first lattice-based folding protocol based on the Module SIS problem. This folding protocol naturally leads to an efficient recursive lattice-based SNARK and an efficient PCD scheme. LatticeFold supports folding low-degree relations, such as R1CS, as well as high-degree relations, such as CCS. The key challenge is to construct a secure folding protocol that works with the Ajtai commitment scheme. The difficulty, is ensuring that extracted witnesses are low norm through many rounds of folding. We present a novel technique using the sumcheck protocol to ensure that extracted witnesses are always low norm no matter how many rounds of folding are used. Our evaluation of the final proof system suggests that it is as performant as Hypernova, while providing post-quantum security.
Paper Link: https://eprint.iacr.org/2024/257
5th LF Energy Power Grid Model Meet-up SlidesDanBrown980551
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
Introduction of Cybersecurity with OSS at Code Europe 2024Hiroshi SHIBATA
I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
The Microsoft 365 Migration Tutorial For Beginner.pptxoperationspcvita
This presentation will help you understand the power of Microsoft 365. However, we have mentioned every productivity app included in Office 365. Additionally, we have suggested the migration situation related to Office 365 and how we can help you.
You can also read: https://www.systoolsgroup.com/updates/office-365-tenant-to-tenant-migration-step-by-step-complete-guide/
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdfChart Kalyan
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
Algorithmen zum Verkleinern von digitalen Videos
1. Algorithmen zum Verkleinern von digitalen Videos
Wolfgang Effelsberg
Praktische Informatik IV
Universität Mannheim
Germany
2. Content
1. Motivation
2. Scaling und Cropping
3. Seam Carving for Still Images
4. An Improvement for Diagonal Lines
5. Seam Carving for Video
6. Conclusion and Outlook
Algorithmen zum Verkleinern Klagenfurt
Wolfgang Effelsberg 2
von digitalen Videos 23. Juli 2012
3. 1. Motivation
• Mobile devices (smart phones, pad computers) are getting very popular for
showing videos.
• The representation of still images and videos on those devices requires an
adaptation to the screen size and the aspect ratio.
• Scaling and Cropping are easy to implement but they do not work very
well.
• Seam Carving is a promising technology for still images and videos.
Algorithmen zum Verkleinern Klagenfurt
Wolfgang Effelsberg 3
von digitalen Videos 23. Juli 2012
4. 2. Scaling and Cropping
Scaling
Scaling reduces the image linearly, without looking at its content.
„Letterboxing“ is used if the format does not fit on the screen.
Example:
Algorithmen zum Verkleinern Klagenfurt
Wolfgang Effelsberg 4
von digitalen Videos 23. Juli 2012
5. Cropping
Cropping cuts the image parallel to the edges until the final format is reached,
without looking at the image content. Parts of the image can get lost.
Example:
Algorithmen zum Verkleinern Klagenfurt
Wolfgang Effelsberg 5
von digitalen Videos 23. Juli 2012
6. 3. Seam Carving for Still Images
Removing of specific pixels from the image, based on the importance of the
content
Based on an „energy function“ describing the importance of different parts of the
content
Algorithmen zum Verkleinern Klagenfurt
Wolfgang Effelsberg 6
von digitalen Videos 23. Juli 2012
7. Example
Reduce the width by 40 %
Energy is maximal on edge pixels in the image.
original image energy image
Algorithmen zum Verkleinern Klagenfurt
Wolfgang Effelsberg 7
von digitalen Videos 23. Juli 2012
8. Naive Approach
Remove from each line the pixels with minimal energy
original image 200 pixels removed
Algorithmen zum Verkleinern Klagenfurt
Wolfgang Effelsberg 8
von digitalen Videos 23. Juli 2012
9. Remove Entire Columns
Remove the 200 columns with the smallest energy
original image 200 columns with minimal
energy removed
Algorithmen zum Verkleinern Klagenfurt
Wolfgang Effelsberg 9
von digitalen Videos 23. Juli 2012
10. Definition of a Seam
• A vertical seam is an 8-connected path of pixels, running from the top to the bottom
of the image and containing exactly one pixel per row.
• Horizontal seams are defined analogously.
Algorithmen zum Verkleinern Klagenfurt
Wolfgang Effelsberg 10
von digitalen Videos 23. Juli 2012
11. Advantage of Seams
Can be adapted better to the regions of interest (regions of high energy)
Algorithmen zum Verkleinern Klagenfurt
Wolfgang Effelsberg 11
von digitalen Videos 23. Juli 2012
12. Seams for our Example
200 vertical seams with minimal energy removed
original image 200 vertical seams removed
Algorithmen zum Verkleinern Klagenfurt
Wolfgang Effelsberg 12
von digitalen Videos 23. Juli 2012
13. Our Other Example
It os obvious that seam carving removes unimportant content first.
Algorithmen zum Verkleinern Klagenfurt
Wolfgang Effelsberg 13
von digitalen Videos 23. Juli 2012
14. Energy Functions (1)
A simple energy function based on the difference in light intensity between two pixels
δ δ
e( I ( x, y )) = I ( x, y ) + I ( x, y )
δx δy
Better (but more complicated) energy functions are possible, for example, based on
important objects found in the image.
Algorithmen zum Verkleinern Klagenfurt
Wolfgang Effelsberg 14
von digitalen Videos 23. Juli 2012
15. Energy Functions (2)
We use saliency and face recognition to identify regions of interest
δ δ
esal + face ( x, y ) = ws ⋅ saliency ( x, y ) + w f ⋅ face( x, y ) + I ( x, y ) + I ( x, y )
δx δy
original image saliency map face map seams with esal+face new
as energy function image
Algorithmen zum Verkleinern Klagenfurt
Wolfgang Effelsberg 15
von digitalen Videos 23. Juli 2012
16. 4. An Improvement for Diagonal Lines
A problem with traditional seam carving: diagonal lines
original image width reduced to 40% by
seam carving
Algorithmen zum Verkleinern Klagenfurt
Wolfgang Effelsberg 16
von digitalen Videos 23. Juli 2012
17. The Problem with Diagonal Lines (1)
When a seam crosses a diagonal line visible artefacts appear.
a diagonal line seams cutting that line seams removed
Algorithmen zum Verkleinern Klagenfurt
Wolfgang Effelsberg 17
von digitalen Videos 23. Juli 2012
18. The Problem with Diagonal Lines (2)
Especially critical if several seams cross the line at the same place.
Idea: distribute the seams more evenly over the line.
Neigboring seams line after removing distribute seams evenly line after removing
cutting a line the seams the seams
Algorithmen zum Verkleinern Klagenfurt
Wolfgang Effelsberg 18
von digitalen Videos 23. Juli 2012
19. Solution for Diagonal Lines (1)
Solution: modify the energy function between the computation of the seams: increase
the energy at intersection points
seam cutting a line modified energy energy function third seam
function and new modified again
seam
Algorithmen zum Verkleinern Klagenfurt
Wolfgang Effelsberg 19
von digitalen Videos 23. Juli 2012
20. Solution for Diagonal Lines (2)
Result
original image traditional seam carving improved seam carving
Algorithmen zum Verkleinern Klagenfurt
Wolfgang Effelsberg 20
von digitalen Videos 23. Juli 2012
21. 5. Seam Carving for Video
First idea: apply seam carving for each frame separately
the video gets shaky.
original video seam carved for each frame separately
Algorithmen zum Verkleinern Klagenfurt
Wolfgang Effelsberg 21
von digitalen Videos 23. Juli 2012
22. Seam Carving for Video: First Idea
The video frames define a 3D block over time.
We remove 2D “seam surfaces”. The seam pixels of one surface are connected in
the third dimension.
We use a graph algorithm (min-cut max-flow) to discover optimal “seam surfaces”.
Problem: takes considerable time to compute.
time
Algorithmen zum Verkleinern Klagenfurt
Wolfgang Effelsberg 22
von digitalen Videos 23. Juli 2012
23. Seam Carving for Videos: Second Idea
Fast seam carving for video
• Accumulate all energy values of all frames in the first frame.
• Compute the optimal seams there.
• Map those seams back to the block of frames.
Algorithmen zum Verkleinern Klagenfurt
Wolfgang Effelsberg 23
von digitalen Videos 23. Juli 2012
24. Example for the Second Idea
seams carved separately fast seam carving
for each frame
Algorithmen zum Verkleinern Klagenfurt
Wolfgang Effelsberg 24
von digitalen Videos 23. Juli 2012
25. Another Example
scaling fast seam carving
Algorithmen zum Verkleinern Klagenfurt
Wolfgang Effelsberg 25
von digitalen Videos 23. Juli 2012
26. 6. Conclusions and Outlook
• Seam Carving is a useful technique to reduce image sizes without losing
relevant content.
• Finding a good energy function is a real challenge.
• Improvements are possible for diagonal lines.
• Flicker removal is of critical importance for videos. Fast Seam Carving is
a useful algorithm for that problem.
• Seam carving does not work well if most of the content is relevant for the
viewer.
• Seam Carving can be combined with other techniques to create pleasant
smal-screen versions of video.
Algorithmen zum Verkleinern Klagenfurt
Wolfgang Effelsberg 26
von digitalen Videos 23. Juli 2012
27. Vielen Dank …
… für Ihre Aufmerksamkeit!
Meine Mailadresse ist
effelsberg@informatik.uni-mannheim.de
Algorithmen zum Verkleinern Klagenfurt
Wolfgang Effelsberg 27
von digitalen Videos 23. Juli 2012