In today’s Adobe Photoshop video tutorial I’m going to take you through my process of creating a vintage style advertisement poster with letterpress print effects. We’ll start by laying out the design with a selection of fonts inspired by the era of wood type, along with some hand-drawn graphic elements using a limited 3-colour palette. […]

The post Video Tutorial: Vintage Letterpress Poster Design in Photoshop appeared first on Spoon Graphics.

For years the only bit of feedback web developers could get was via alert("{str}") calls. These days we have the web console but, in rare cases, we don’t have a console and alert calls are our only window into a value at a given time. One problem: if an alert sneaks into production code, your […]

The post Override window.alert appeared first on David Walsh Blog.

Access management can be a bit of a nightmare, especially when we realize that we rely on a number of different, independent services that power our organizations. Many businesses use Gmail for email, Google Docs for documents, Slack for communication, GitHub for their codebase, etc. Yet each of these services provides their own permissions screens, […]

The post Teamstack: Easy Automation of Identity Management (Sponsored) appeared first on David Walsh Blog.

How many of you love wasting hours of time making the same basic edits to a lot of photos? Anyone? No? Well, that’s understandable. None of us like doing menial repetitive tasks and it’s no different when editing images — even for those of us who enjoy the editing process. The good news is that Lightroom has a handy tool Continue Reading

The post How to Use Lightroom Presets- A Handy Guide appeared first on Photodoto.

Have you got yourself a Sony Xperia Z1 Compact but not sure how to do something on it? Don’t worry, we’ve come up with a comprehensive guide for all the things your handset is capable of. Navigate the various sections using the links below. If you can’t find what you’re looking for just leave a … Continue reading Sony Xperia Z1 Compact Complete Guide →

Got a brand new Motorola Moto X but not sure how to do something on it? Fear not as we’ve put together a comprehensive guide to get your started. Scroll through or navigate using the links below, and if you’ve got a query and we havne’t covered it, let us know. Leave us a comment … Continue reading Motorola Moto X complete guide →

Got a Motorola Moto G but not sure how to do something on it? Not to worry as we’ve come up with a comprehensive guide for all the things your handset is capable of doing. Navigate using the links below or download the full guide by clicking on the PDF logo. If you can’t find … Continue reading Motorola Moto G Complete Guide →

Tags: coronavirus, Marcel Salathé, Nicky Case, simulation

“In conceptual art the idea or concept is the most important aspect of the work. When an artist uses a conceptual form of art, it means that all of the planning and decisions are made beforehand and the execution is a perfunctory affair. The idea becomes a machine that makes the art. This kind of art is not theoretical or illustrative of theories; it is intuitive, it is involved with all types of mental processes and it is purposeless. It is usually free from the dependence on the skill of the artist as a craftsman.”

- Artist Sol Lewitt on conceptual art.

If you’re a remote worker, you may have plenty of experience with video conferencing as a way to communicate with clients, team members, or other colleagues. But with millions of additional...

Click through to read the rest of the story on the Vandelay Design Blog.

The galaxy far far away has items both big and small. The Star Wars Size Comparison Video created by MetaBallStudios brings droids, people and planets together from the Star Wars movies (episode I to VIII, Rogue One and Solo). See how your favorites size up against each other.

Comparison of many things from the Star Wars movies. Only movies from episode I to VIII, Rogue One and Solo. Obviously not everything appears, only the most representative.

Providing scale and context to your audience is one of the key tenets of data visualization, and this video does a fantastic job of giving you the context of the size of everything in the Star Wars universe.

Found on Gizmodo.com.

Michiel Dullaert, data visualization expert and trainer from the Netherlands, has updated his Chart Guide poster to version 4! A free PDF is available for download from his website, and introduces a new category, 19 new charts and 4 extra design tips. You can also purchase a full-size printed poster version.

As the November 2019 Giveaway, I have a pair of Chart Guide posters, that will be shipped to one lucky winner. That way you get one for yourself, and one you can give to a friend or coworker.

Register HERE by November 30, 2019 at 11:59pm CT, and the winner will be randomly chosen on December 1st!

This poster shows 84 charts to choose from and includes 16 chart design tips to help you make the Perfect Chart. The poster is available as a big poster or you can download the PDF file for free. Let this ChartGuide poster help you choose and design your Perfect Chart.

You can see his complete write-up about the new version HERE. I was able to ask Michiel a few interview questions about developing the posters:

Cool Infographics: What’s your background and how did you get into visualizing data?

Michiel Dullaert: Years ago I have been working in the boardgame and puzzle industry. Part of my work was discovering new boardgames and puzzles and introduce them to the market. I was working for two different companies, both at the time that a new product of theirs really changed the market. For the boardgame industry I worked for the company that introduced a new type of boardgame (the game of Catan) that made playing boardgames a popular hobby. After that, I worked for a company that created puzzle magazines at the time the Sudoku puzzles was introduced. And here the same happened again, a new type of puzzle that changed the way people would puzzle and talk about puzzles. Both were very nice jobs, with a lot of enthusiastic conversations with customers about new products.

In both companies I was working in the product development. I always had a large personal interest in the data behind the products. So it felt logic to do more with data, and I changed careers. I started working for a large company as an analyst. And it was not long that I found out that my colleagues were not interested in my reports. Although the reports contained interesting information it was shown in large tables and busy charts. People seemed to be not interested and if the looked into the numbers, they did not seem to understand them. My work did not seem to matter. The contrast between my previous jobs and the work as an analyst could not have been bigger. At that time I decided I would try to find a way to make people as enthusiastic about data as they were about boardgames and Sudoku puzzles. 

The first step was reading books on the topic of data visualization. Because I was working in the business intelligence field, the most logic choice were the books of Stephen Few. I bought them all and a whole new world opened for me. When Few was in the Netherlands to give a course I felt very lucky I could join. The workshops inspired me to learn more on this topic. So I bought more books and the next year I joined a class of Alberto Caïro. This gave me multiple perspectives on the same topic. The things I learned were applied to my work, and I was getting more and more responses on my visualizations. People actually started to read and understand them. 

My manager asked me to explain my choices in visualizations to my colleagues, so they could learn from me. And then I discovered how great it is to teach about data visualisation. I met a couple of UX designers and they inspired me learn more about that topic and to get an UX certification. The knowledge I gained in learning UX helped me in developing my own perspective on good data visualization. And in my workshop I try to inspire others to create such. For these workshops I wanted an overview of charts. Although there were already some great overviews, none of them had the point of view I was teaching in class. So I decided to design my own. That’s how Chart.Guide started. 

Cool Infographics: Who is the Chart Guide poster intended for?

Michiel Dullaert: The website and the posters are intended for everyone who makes charts. For me it does not matter if you are working as a data-journalist or a data scientist, a infographic designer, project manager or a financial analyst. As long as you need help or inspiration when making charts or tables, Chart.Guide can help you. Online in the form of the website and offline in the form of the poster. Because I want to inspire as many people as possible I made the PDF of the poster free to download. I know that the poster is used in business departments, newsrooms and in school classrooms.

Cool Infographics: What was your design process for the poster?

Michiel Dullaert: The main source for updates to the poster or website, is the conversations I have with people I teach or work with. If they have a need for certain chart types, or make design mistakes, I try to add that topic. 

The first poster edition (picture DPG Chart Chooser) was just a collection of charts I created for my students. For each chart a few words on when to use the chart and, more important, it gave advice on what charts were not recommended. On the second edition (the first under the Chart.Guide brand) I added chart design tips.  The reason, I saw people choose a good chart but then mess up the design. Last year, I got questions about maps, so I decided to add them on poster edition 4. 

The design process starts with insight I get from conversations I am having. Next step is cutting the old poster and rearranging everything. (see picture ChartGuide rearrange) now, will lead to more insights on the poster in the future. Although it make take some time to transform everything to the screen or paper. I still need to find some time to explain on the website why some charts are “not recommended”. 

Cool Infographics: You asked your followers to help choose the design of the new poster. How did that go?

Michiel Dullaert: The poster is made to help people. So it seems to be logic to give them a role in the design process. As a UX designer I like to test my designs before releasing them. Most of these tests are done in class, because I like to observe the users in how they use the new design. The online voting was suggestion of a student. It did give me a lot of useful feedback. Especially when people wrote a lot of text explaining their choice. For future editions I will do the same.

Cool Infographics: How can people follow you for updates?

Michiel Dullaert: People who have downloaded the PDF will get an email when a new poster is available, or when something interesting is added to the website. For this and more chart related inspiration, they can follow me on Twitter: @Chart_Guide or on facebook: /ChartGuide1.

This helpful reference guide is one of over 25 FREE data visualization guides I maintain links to in the Cool Infographics Tools pages. See them all on the DataViz Reference Guides page, and let me know if I’m missing any.

Visual explanations are a big part of data visualizations, and this video exploration of What’s Inside the White House? by animator Jared Owen gives viewers a great perspective of where the major rooms are located in context with the rest of the building. I would bet that most people don’t know that the Oval Office isn’t in the main, center building.

The White House is full of lots of interesting rooms. A lot of people don't realize that this information is public! Please join me as we take a walk through the different rooms and what they are used for.

Found on Core77

We’re all working from home, and that include job interviews, news interviews, class lectures, webinars, presentations to customers and even just business meetings. The 10 Things to Do Before Any Video Interview infographic from Kickresume is a great last-minute checklist before you turn on your webcam!

In the end, you can take this infographic as a checklist. You can use it to prepare for your job interview or any other video conference call.

And, oh boy, are we going to make many more of those. Sure, it took a global pandemic for companies to recognize the value of working from home but now there’s no going back. Video conference calls are here to stay. (I personally hate it but even I should probably get used to it. Damn.)

Anyway, good luck at your job interview!

I would have preferred more visual elements, but I like that this is a tightly focused infographic with a clear, useful message to a broad audience. This is one of the best uses for an infographic: an informative topic, related to the industry of the publishing company, with a popular, trending topic. This design checks all the boxes.

Designers have to remember that the infographic image file will often be shared by itself, so it always helps to include a few more thins in the footer:

• The Infographic Landing Page URL (not just the company home page). This will help readers find the full infographic and the article that went along with it. Don’t make people search for it on your website.

• A copyright or Creative Commons statement is always a good idea when you publishing an infographic

Center for Biological Diversity Press Release WASHINGTON – Four commonly used neonicotinoid pesticides can harm bees and other pollinators, according to a new analysis by California’s Department of Pesticide Regulation. The study found that current approved uses of the “neonics” … Continue reading →

Intercellar - Accidental Anomalies of Particle Wallpapers

Branding and Visual Identity for Potency Design

Abelardo Morell
Camera Obscura: Early Morning View of the East Side of Midtown Manhattan, , 2014
Website - AbelardoMorell.net

Abelardo Morell was born in Havana, Cuba in 1948. He immigrated to the United States with his parents in 1962. Morell received his undergraduate degree in 1977 from Bowdoin College and an MFA from The Yale University School of Art in 1981. In 1997 he received an honorary degree from Bowdoin College.

His publications include a photographic illustration of Alice’s Adventures in Wonderland (1998) by Dutton Children’s Books, A Camera in a Room (1995) by Smithsonian Press, A Book of Books (2002) and Camera Obscura (2004) by Bulfinch Press and Abelardo Morell (2005), published by Phaidon Press. Recent publications include a limited edition book by The Museum of Modern Art in New York of his Cliché Verre images with a text by Oliver Sacks.

His work has been collected and shown in many galleries, institutions and museums, including the Museum of Modern Art, The Whitney Museum of American Art, the Metropolitan Art Museum in New York, The Chicago Art Institute, The San Francisco Museum of Modern Art, The Houston Museum of Art, The Boston Museum of Fine Art, The Victoria & Albert Museum and over seventy other museums in the United States and abroad. A retrospective of his work organized jointly by the Art Institute of Chicago, The Getty in Los Angeles and The High Museum in Atlanta closed in May 2014 after a year of travel. Abelardo will be having his first show at the Edwynn Houk Gallery in New York opening October 23, 2014 and will run until December 20, 2014 featuring a selection of new pictures.

When you want to succeed in the organic search engine results today, you have to focus on your website and learn what you should do to optimize it. There are many factors that can help you with that, form the technical, off-page, and on-page. All these factors and parts of a website require updating and […]

Original post: 10 On-Page SEO Factors You Should Consider [2019]

The post 10 On-Page SEO Factors You Should Consider [2019] appeared first on Daily Blog Tips.

A nearly two-minute, profanity-laced tirade at a code officer at a Miami Beach grocery store is the latest example of mounting tensions in the US over wearing masks to stem the spread of the coronavirus.

Chris Guillebeau has traveled to 193 countries. And just to be clear, that is all of the countries recognized on the planet. He is the first person to do it before the age of 35. More importantly, he has built online businesses, side hustles, and mastered the art of a non-conforming lifestyle since he was 19 years old. There’s almost nobody better person equipped to talk about starting lots of businesses. He has a daily podcast called Side Hustle School where he’s featured more than 850 different side hustle businesses + featured many in his new book called 100 Side Hustles. Chris also started half a dozen or more himself, started one of my favorite conferences, The World Domination Summit, and is a New York Times bestselling author of books like the $100 Start Up and The Art of Non-Conformity and many others. This guy is a beast and he’s so savvy, so humble. In this episode: We go into details about some of Chris’ favorite side hustle businesses he’s come across in his podcast & writing this book – what are some of the most common traits and failures. Chris shares his experience with depression, how he’s faced it, […]

The post Adaptation, Self-Awareness and Art of the Side Hustle with Chris Guillebeau appeared first on Chase Jarvis Photography.

In this episode I’m chatting with my long time friend and financial guru, Ramit Sethi. Ramit has been on the show a number of times, and this time we’re connecting virtually from our living rooms during the quarantine. Of course we get into finances during these uncertain times, but more importantly: adaptation and resilience. Over the years, no one has single-handedly given me better insight about the business side of art than the New York Times bestselling author, Ramit Sethi. Take a listen and let us know what you think. Enjoy! This episode was part of CreativeLive TV, a brand-new, free, 24/7 variety show, live-streamed from the very casual living rooms, studios, and kitchen tables of our worldwide community of legendary creators. You can expect musical performances, Q&As, cooking, spoken word, drawing, and more – featuring many of our favorite personalities – all in a safe, virtual space full of joy, shared experiences, and connection via live, interactive chat. The schedule and upcoming broadcasts can be seen at http://creativelive.com/tv FOLLOW RAMIT: instagram | twitter | website Listen to the Podcast  Subscribe   Watch the Episode This podcast is brought to you by CreativeLive. CreativeLive is the world’s largest hub […]

The post Finance Fireside Chat with Ramit Sethi appeared first on Chase Jarvis Photography.

Increases time on page and boosts engagement with your site Thanks to the ever-increasing internet speeds, videos are in high demand. Right now, video is everywhere on social media, websites, and apps. We are watching them on all our screens, desktops, tablets, phones and smart TVs. It is expected a growth in video content up …

Wix Video — a great marketing tool for any website. Read More »

About six years ago, a colleague I’ll call Tom, because that’s his name, forwarded me a link to the ‘WASD CODE’; a keyboard focused on the needs of programmers, designed with the help of Stack Overflow’s Jeff Atwood. I had no idea at the time that there were people actually dedicating themselves to creating keyboards beyond the stock fare shipping with computers. As I read and re-read the blurb, I was smitten.

How we read pie charts is still an open question: is it angle? Is it area? Is it arc length? In a study I'm presenting as a short paper at the IEEE VIS conference in Vancouver next week, I tried to tease the visual cues apart – using modeling and 3D pie charts. The big […]

Let $1 le r < n$ be integers. We give a proof that the group $mathop{mathrm{Aut}}({X_{n}^{mathbb{N}}, sigma_{n}})$ of automorphisms of the one-sided shift on $n$ letters embeds naturally as a subgroup $mathcal{h}_{n}$ of the outer automorphism group $mathop{mathrm{Out}}(G_{n,r})$ of the Higman-Thompson group $G_{n,r}$. From this, we can represent the elements of $mathop{mathrm{Aut}}({X_{n}^{mathbb{N}}, sigma_{n}})$ by finite state non-initial transducers admitting a very strong synchronizing condition.

Let $H in mathcal{H}_{n}$ and write $|H|$ for the number of states of the minimal transducer representing $H$. We show that $H$ can be written as a product of at most $|H|$ torsion elements. This result strengthens a similar result of Boyle, Franks and Kitchens, where the decomposition involves more complex torsion elements and also does not support practical extit{a priori} estimates of the length of the resulting product.

We also give new proofs of some known results about $mathop{mathrm{Aut}}({X_{n}^{mathbb{N}}, sigma_{n}})$.

This paper addresses the problem of identifying the graph structure of a dynamical network using measured input/output data. This problem is known as topology identification and has received considerable attention in recent literature. Most existing literature focuses on topology identification for networks with node dynamics modeled by single integrators or single-input single-output (SISO) systems. The goal of the current paper is to identify the topology of a more general class of heterogeneous networks, in which the dynamics of the nodes are modeled by general (possibly distinct) linear systems. Our two main contributions are the following. First, we establish conditions for topological identifiability, i.e., conditions under which the network topology can be uniquely reconstructed from measured data. We also specialize our results to homogeneous networks of SISO systems and we will see that such networks have quite particular identifiability properties. Secondly, we develop a topology identification method that reconstructs the network topology from input/output data. The solution of a generalized Sylvester equation will play an important role in our identification scheme.

In this paper we consider the "quasidensity" of a subset of the product of a Banach space and its dual, and give a connection between quasidense sets and sets of "type (NI)". We discuss "coincidence sets" of certain convex functions and prove two sum theorems for coincidence sets. We obtain new results on the Fitzpatrick extension of a closed quasidense monotone multifunction. The analysis in this paper is self-contained, and independent of previous work on "Banach SN spaces". This version differs from the previous version because it is shown that the (well known) equivalence of quasidensity and "type (NI)" for maximally monotone sets is not true without the monotonicity assumption and that the appendix has been moved to the end of Section 10, where it rightfully belongs.

This paper develops a method for obtaining guaranteed outer approximations for global attractors of continuous and discrete time nonlinear dynamical systems. The method is based on a hierarchy of semidefinite programming problems of increasing size with guaranteed convergence to the global attractor. The approach taken follows an established line of reasoning, where we first characterize the global attractor via an infinite dimensional linear programming problem (LP) in the space of Borel measures. The dual to this LP is in the space of continuous functions and its feasible solutions provide guaranteed outer approximations to the global attractor. For systems with polynomial dynamics, a hierarchy of finite-dimensional sum-of-squares tightenings of the dual LP provides a sequence of outer approximations to the global attractor with guaranteed convergence in the sense of volume discrepancy tending to zero. The method is very simple to use and based purely on convex optimization. Numerical examples with the code available online demonstrate the method.

Given a standard graded polynomial ring over a commutative Noetherian ring $A$, we prove that the cohomological dimension and the height of the ideals defining any of its Veronese subrings are equal. This result is due to Ogus when $A$ is a field of characteristic zero, and follows from a result of Peskine and Szpiro when $A$ is a field of positive characteristic; our result applies, for example, when $A$ is the ring of integers.

With the increase in use of Unmanned Aerial Vehicles (UAVs)/drones, it is important to detect and identify causes of failure in real time for proper recovery from a potential crash-like scenario or post incident forensics analysis. The cause of crash could be either a fault in the sensor/actuator system, a physical damage/attack, or a cyber attack on the drone's software. In this paper, we propose novel architectures based on deep Convolutional and Long Short-Term Memory Neural Networks (CNNs and LSTMs) to detect (via Autoencoder) and classify drone mis-operations based on sensor data. The proposed architectures are able to learn high-level features automatically from the raw sensor data and learn the spatial and temporal dynamics in the sensor data. We validate the proposed deep-learning architectures via simulations and experiments on a real drone. Empirical results show that our solution is able to detect with over 90% accuracy and classify various types of drone mis-operations (with about 99% accuracy (simulation data) and upto 88% accuracy (experimental data)).

Recent single image unsupervised representation learning techniques show remarkable success on a variety of tasks. The basic principle in these works is instance discrimination: learning to differentiate between two augmented versions of the same image and a large batch of unrelated images. Networks learn to ignore the augmentation noise and extract semantically meaningful representations. Prior work uses artificial data augmentation techniques such as cropping, and color jitter which can only affect the image in superficial ways and are not aligned with how objects actually change e.g. occlusion, deformation, viewpoint change. In this paper, we argue that videos offer this natural augmentation for free. Videos can provide entirely new views of objects, show deformation, and even connect semantically similar but visually distinct concepts. We propose Video Noise Contrastive Estimation, a method for using unlabeled video to learn strong, transferable single image representations. We demonstrate improvements over recent unsupervised single image techniques, as well as over fully supervised ImageNet pretraining, across a variety of temporal and non-temporal tasks. Code and the Random Related Video Views dataset are available at https://www.github.com/danielgordon10/vince

Introduction of spectrum-sharing in 5G and subsequent generation networks demand base-station(s) with the capability to characterize the wideband spectrum spanned over licensed, shared and unlicensed non-contiguous frequency bands. Spectrum characterization involves the identification of vacant bands along with center frequency and parameters (energy, modulation, etc.) of occupied bands. Such characterization at Nyquist sampling is area and power-hungry due to the need for high-speed digitization. Though sub-Nyquist sampling (SNS) offers an excellent alternative when the spectrum is sparse, it suffers from poor performance at low signal to noise ratio (SNR) and demands careful design and integration of digital reconstruction, tunable channelizer and characterization algorithms. In this paper, we propose a novel deep-learning framework via a single unified pipeline to accomplish two tasks: 1)~Reconstruct the signal directly from sub-Nyquist samples, and 2)~Wideband spectrum characterization. The proposed approach eliminates the need for complex signal conditioning between reconstruction and characterization and does not need complex tunable channelizers. We extensively compare the performance of our framework for a wide range of modulation schemes, SNR and channel conditions. We show that the proposed framework outperforms existing SNS based approaches and characterization performance approaches to Nyquist sampling-based framework with an increase in SNR. Easy to design and integrate along with a single unified deep learning framework make the proposed architecture a good candidate for reconfigurable platforms.

Histopathology is a reflection of the molecular changes and provides prognostic phenotypes representing the disease progression. In this study, we introduced feature scores generated from hematoxylin and eosin histology images based on deep learning (DL) models developed for prostate pathology. We demonstrated that these feature scores were significantly prognostic for time to event endpoints (biochemical recurrence and cancer-specific survival) and had simultaneously molecular biologic associations to relevant genomic alterations and molecular subtypes using already trained DL models that were not previously exposed to the datasets of the current study. Further, we discussed the potential of such feature scores to improve the current tumor grading system and the challenges that are associated with tumor heterogeneity and the development of prognostic models from histology images. Our findings uncover the potential of feature scores from histology images as digital biomarkers in precision medicine and as an expanding utility for digital pathology.

For real-time semantic video segmentation, most recent works utilised a dynamic framework with a key scheduler to make online key/non-key decisions. Some works used a fixed key scheduling policy, while others proposed adaptive key scheduling methods based on heuristic strategies, both of which may lead to suboptimal global performance. To overcome this limitation, we model the online key decision process in dynamic video segmentation as a deep reinforcement learning problem and learn an efficient and effective scheduling policy from expert information about decision history and from the process of maximising global return. Moreover, we study the application of dynamic video segmentation on face videos, a field that has not been investigated before. By evaluating on the 300VW dataset, we show that the performance of our reinforcement key scheduler outperforms that of various baselines in terms of both effective key selections and running speed. Further results on the Cityscapes dataset demonstrate that our proposed method can also generalise to other scenarios. To the best of our knowledge, this is the first work to use reinforcement learning for online key-frame decision in dynamic video segmentation, and also the first work on its application on face videos.

Compromised accounts on social networks are regular user accounts that have been taken over by an entity with malicious intent. Since the adversary exploits the already established trust of a compromised account, it is crucial to detect these accounts to limit the damage they can cause. We propose a novel general framework for discovering compromised accounts by semantic analysis of text messages coming out from an account. Our framework is built on the observation that normal users will use language that is measurably different from the language that an adversary would use when the account is compromised. We use our framework to develop specific algorithms that use the difference of language models of users and adversaries as features in a supervised learning setup. Evaluation results show that the proposed framework is effective for discovering compromised accounts on social networks and a KL-divergence-based language model feature works best.

Domain of mathematical logic in computers is dominated by automated theorem provers (ATP) and interactive theorem provers (ITP). Both of these are hard to access by AI from the human-imitation approach: ATPs often use human-unfriendly logical foundations while ITPs are meant for formalizing existing proofs rather than problem solving. We aim to create a simple human-friendly logical system for mathematical problem solving. We picked the case study of Euclidean geometry as it can be easily visualized, has simple logic, and yet potentially offers many high-school problems of various difficulty levels. To make the environment user friendly, we abandoned strict logic required by ITPs, allowing to infer topological facts from pictures. We present our system for Euclidean geometry, together with a graphical application GeoLogic, similar to GeoGebra, which allows users to interactively study and prove properties about the geometrical setup.

Image-based tracking of medical instruments is an integral part of many surgical data science applications. Previous research has addressed the tasks of detecting, segmenting and tracking medical instruments based on laparoscopic video data. However, the methods proposed still tend to fail when applied to challenging images and do not generalize well to data they have not been trained on. This paper introduces the Heidelberg Colorectal (HeiCo) data set - the first publicly available data set enabling comprehensive benchmarking of medical instrument detection and segmentation algorithms with a specific emphasis on robustness and generalization capabilities of the methods. Our data set comprises 30 laparoscopic videos and corresponding sensor data from medical devices in the operating room for three different types of laparoscopic surgery. Annotations include surgical phase labels for all frames in the videos as well as instance-wise segmentation masks for surgical instruments in more than 10,000 individual frames. The data has successfully been used to organize international competitions in the scope of the Endoscopic Vision Challenges (EndoVis) 2017 and 2019.

Neural style transfer is a well-known branch of deep learning research, with many interesting works and two major drawbacks. Most of the works in the field are hard to use by non-expert users and substantial hardware resources are required. In this work, we present a solution to both of these problems. We have applied neural style transfer to real-time video (over 25 frames per second), which is capable of running on mobile devices. We also investigate the works on achieving temporal coherence and present the idea of fine-tuning, already trained models, to achieve stable video. What is more, we also analyze the impact of the common deep neural network architecture on the performance of mobile devices with regard to number of layers and filters present. In the experiment section we present the results of our work with respect to the iOS devices and discuss the problems present in current Android devices as well as future possibilities. At the end we present the qualitative results of stylization and quantitative results of performance tested on the iPhone 11 Pro and iPhone 6s. The presented work is incorporated in Kunster - AR Art Video Maker application available in the Apple's App Store.

Diagnosis of high impedance fault (HIF) is a challenge for nowadays distribution network protections. The fault current of a HIF is much lower than that of a normal load, and fault feature is significantly affected by fault scenarios. A detection and feeder identification algorithm for HIFs is proposed in this paper, based on the high-resolution and synchronous waveform data. In the algorithm, an interval slope is defined to describe the waveform distortions, which guarantees a uniform feature description under various HIF nonlinearities and noise interferences. For three typical types of network neutrals, i.e.,isolated neutral, resonant neutral, and low-resistor-earthed neutral, differences of the distorted components between the zero-sequence currents of healthy and faulty feeders are mathematically deduced, respectively. As a result, the proposed criterion, which is based on the distortion relationships between zero-sequence currents of feeders and the zero-sequence voltage at the substation, is theoretically supported. 28 HIFs grounded to various materials are tested in a 10kV distribution networkwith three neutral types, and are utilized to verify the effectiveness of the proposed algorithm.

This paper provides a method for the simultaneous topology optimization of parts and their corresponding joint locations in an assembly. Therein, the joint locations are not discrete and predefined, but continuously movable. The underlying coupling equations allow for connecting dissimilar meshes and avoid the need for remeshing when joint locations change. The presented method models the force transfer at a joint location not only by using single spring elements but accounts for the size and type of the joints. When considering riveted or bolted joints, the local part geometry at the joint location consists of holes that are surrounded by material. For spot welds, the joint locations are filled with material and may be smaller than for bolts. The presented method incorporates these material and clearance zones into the simultaneously running topology optimization of the parts. Furthermore, failure of joints may be taken into account at the optimization stage, yielding assemblies connected in a fail-safe manner.

Any media experience must be fully inclusive and accessible to all users regardless of their ability. With the current trend towards immersive experiences, such as Virtual Reality (VR) and 360-degree video, it becomes key that these environments are adapted to be fully accessible. However, until recently the focus has been mostly on adapting the existing techniques to fit immersive displays, rather than considering new approaches for accessibility designed specifically for these increasingly relevant media experiences. This paper surveys a wide range of 360-degree video players and examines the features they include for dealing with accessibility, such as Subtitles, Audio Description, Sign Language, User Interfaces, and other interaction features, like voice control and support for multi-screen scenarios. These features have been chosen based on guidelines from standardization contributions, like in the World Wide Web Consortium (W3C) and the International Communication Union (ITU), and from research contributions for making 360-degree video consumption experiences accessible. The in-depth analysis has been part of a research effort towards the development of a fully inclusive and accessible 360-degree video player. The paper concludes by discussing how the newly developed player has gone above and beyond the existing solutions and guidelines, by providing accessibility features that meet the expectations for a widely used immersive medium, like 360-degree video.

Thin structures, such as wire-frame sculptures, fences, cables, power lines, and tree branches, are common in the real world.

It is extremely challenging to acquire their 3D digital models using traditional image-based or depth-based reconstruction methods because thin structures often lack distinct point features and have severe self-occlusion.

We propose the first approach that simultaneously estimates camera motion and reconstructs the geometry of complex 3D thin structures in high quality from a color video captured by a handheld camera.

Specifically, we present a new curve-based approach to estimate accurate camera poses by establishing correspondences between featureless thin objects in the foreground in consecutive video frames, without requiring visual texture in the background scene to lock on.

Enabled by this effective curve-based camera pose estimation strategy, we develop an iterative optimization method with tailored measures on geometry, topology as well as self-occlusion handling for reconstructing 3D thin structures.

Extensive validations on a variety of thin structures show that our method achieves accurate camera pose estimation and faithful reconstruction of 3D thin structures with complex shape and topology at a level that has not been attained by other existing reconstruction methods.

Previous methods on estimating detailed human depth often require supervised training with `ground truth' depth data. This paper presents a self-supervised method that can be trained on YouTube videos without known depth, which makes training data collection simple and improves the generalization of the learned network. The self-supervised learning is achieved by minimizing a photo-consistency loss, which is evaluated between a video frame and its neighboring frames warped according to the estimated depth and the 3D non-rigid motion of the human body. To solve this non-rigid motion, we first estimate a rough SMPL model at each video frame and compute the non-rigid body motion accordingly, which enables self-supervised learning on estimating the shape details. Experiments demonstrate that our method enjoys better generalization and performs much better on data in the wild.

Despite recent progress on computer vision and natural language processing, developing video understanding intelligence is still hard to achieve due to the intrinsic difficulty of story in video. Moreover, there is not a theoretical metric for evaluating the degree of video understanding. In this paper, we propose a novel video question answering (Video QA) task, DramaQA, for a comprehensive understanding of the video story. The DramaQA focused on two perspectives: 1) hierarchical QAs as an evaluation metric based on the cognitive developmental stages of human intelligence. 2) character-centered video annotations to model local coherence of the story. Our dataset is built upon the TV drama "Another Miss Oh" and it contains 16,191 QA pairs from 23,928 various length video clips, with each QA pair belonging to one of four difficulty levels. We provide 217,308 annotated images with rich character-centered annotations, including visual bounding boxes, behaviors, and emotions of main characters, and coreference resolved scripts. Additionally, we provide analyses of the dataset as well as Dual Matching Multistream model which effectively learns character-centered representations of video to answer questions about the video. We are planning to release our dataset and model publicly for research purposes and expect that our work will provide a new perspective on video story understanding research.

We propose Cotatron, a transcription-guided speech encoder for speaker-independent linguistic representation. Cotatron is based on the multispeaker TTS architecture and can be trained with conventional TTS datasets. We train a voice conversion system to reconstruct speech with Cotatron features, which is similar to the previous methods based on Phonetic Posteriorgram (PPG). By training and evaluating our system with 108 speakers from the VCTK dataset, we outperform the previous method in terms of both naturalness and speaker similarity. Our system can also convert speech from speakers that are unseen during training, and utilize ASR to automate the transcription with minimal reduction of the performance. Audio samples are available at https://mindslab-ai.github.io/cotatron, and the code with a pre-trained model will be made available soon.

Automated person re-identification in a multi-camera surveillance setup is very important for effective tracking and monitoring crowd movement. In the recent years, few deep learning based re-identification approaches have been developed which are quite accurate but time-intensive, and hence not very suitable for practical purposes. In this paper, we propose an efficient hierarchical re-identification approach in which color histogram based comparison is first employed to find the closest matches in the gallery set, and next deep feature based comparison is carried out using Siamese network. Reduction in search space after the first level of matching helps in achieving a fast response time as well as improving the accuracy of prediction by the Siamese network by eliminating vastly dissimilar elements. A silhouette part-based feature extraction scheme is adopted in each level of hierarchy to preserve the relative locations of the different body structures and make the appearance descriptors more discriminating in nature. The proposed approach has been evaluated on five public data sets and also a new data set captured by our team in our laboratory. Results reveal that it outperforms most state-of-the-art approaches in terms of overall accuracy.

Chest computed tomography (CT) becomes an effective tool to assist the diagnosis of coronavirus disease-19 (COVID-19). Due to the outbreak of COVID-19 worldwide, using the computed-aided diagnosis technique for COVID-19 classification based on CT images could largely alleviate the burden of clinicians. In this paper, we propose an Adaptive Feature Selection guided Deep Forest (AFS-DF) for COVID-19 classification based on chest CT images. Specifically, we first extract location-specific features from CT images. Then, in order to capture the high-level representation of these features with the relatively small-scale data, we leverage a deep forest model to learn high-level representation of the features. Moreover, we propose a feature selection method based on the trained deep forest model to reduce the redundancy of features, where the feature selection could be adaptively incorporated with the COVID-19 classification model. We evaluated our proposed AFS-DF on COVID-19 dataset with 1495 patients of COVID-19 and 1027 patients of community acquired pneumonia (CAP). The accuracy (ACC), sensitivity (SEN), specificity (SPE) and AUC achieved by our method are 91.79%, 93.05%, 89.95% and 96.35%, respectively. Experimental results on the COVID-19 dataset suggest that the proposed AFS-DF achieves superior performance in COVID-19 vs. CAP classification, compared with 4 widely used machine learning methods.