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3 methodologies for automated video game highlight detection and capture

With the rise of livestreaming, gaming has evolved from a toy-like consumer product to a legitimate platform and medium in its own right for entertainment and competition.

Twitch’s viewer base alone has grown from 250,000 average concurrent viewers to over 3 million since its acquisition by Amazon in 2014. Competitors like Facebook Gaming and YouTube Live are following similar trajectories.

The boom in viewership has fueled an ecosystem of supporting products as today’s professional streamers push technology to its limit to increase the production value of their content and automate repetitive aspects of the video production cycle.

The largest streamers hire teams of video editors and social media managers, but growing and part-time streamers struggle to do this themselves or come up with the money to outsource it.

The online streaming game is a grind, with full-time creators putting in eight- if not 12-hour performances on a daily basis. In a bid to capture valuable viewer attention, 24-hour marathon streams are not uncommon either.

However, these hours in front of the camera and keyboard are only half of the streaming grind. Maintaining a constant presence on social media and YouTube fuels the growth of the stream channel and attracts more viewers to catch a stream live, where they may purchase monthly subscriptions, donate and watch ads.

Distilling the most impactful five to 10 minutes of content out of eight or more hours of raw video becomes a non-trivial time commitment. At the top of the food chain, the largest streamers can hire teams of video editors and social media managers to tackle this part of the job, but growing and part-time streamers struggle to find the time to do this themselves or come up with the money to outsource it. There aren’t enough minutes in the day to carefully review all the footage on top of other life and work priorities.

Computer vision analysis of game UI

An emerging solution is to use automated tools to identify key moments in a longer broadcast. Several startups compete to dominate this emerging niche. Differences in their approaches to solving this problem are what differentiate competing solutions from each other. Many of these approaches follow a classic computer science hardware-versus-software dichotomy.

Athenascope was one of the first companies to execute on this concept at scale. Backed by $2.5 million of venture capital funding and an impressive team of Silicon Valley Big Tech alumni, Athenascope developed a computer vision system to identify highlight clips within longer recordings.

In principle, it’s not so different from how self-driving cars operate, but instead of using cameras to read nearby road signs and traffic lights, the tool captures the gamer’s screen and recognizes indicators in the game’s user interface that communicate important events happening in-game: kills and deaths, goals and saves, wins and losses.

These are the same visual cues that traditionally inform the game’s player what is happening in the game. In modern game UIs, this information is high-contrast, clear and unobscured, and typically located in predictable, fixed locations on the screen at all times. This predictability and clarity lends itself extremely well to computer vision techniques such as optical character recognition (OCR) — reading text from an image.

The stakes here are lower than self-driving cars, too, since a false positive from this system produces nothing more than a less-exciting-than-average video clip — not a car crash.

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AI-driven audio cloning startup gives voice to Einstein chatbot

You’ll need to prick up your ears for this slice of deepfakery emerging from the wacky world of synthesized media: A digital version of Albert Einstein — with a synthesized voice that’s been (re)created using AI voice cloning technology drawing on audio recordings of the famous scientist’s actual voice.

The startup behind the “uncanny valley” audio deepfake of Einstein is Aflorithmic (whose seed round we covered back in February).

While the video engine powering the 3D character rending components of this “digital human” version of Einstein is the work of another synthesized media company — UneeQ — which is hosting the interactive chatbot version on its website.

Alforithmic says the “digital Einstein” is intended as a showcase for what will soon be possible with conversational social commerce. Which is a fancy way of saying deepfakes that make like historical figures will probably be trying to sell you pizza soon enough, as industry watchers have presciently warned.

The startup also says it sees educational potential in bringing famous, long-deceased figures to interactive “life”.

Or, well, an artificial approximation of it — the “life” being purely virtual and Digital Einstein’s voice not being a pure tech-powered clone either; Alforithmic says it also worked with an actor to do voice modelling for the chatbot (because how else was it going to get Digital Einstein to be able to say words the real-deal would never even have dreamt of saying — like, er, “blockchain”?). So there’s a bit more than AI artifice going on here too.

“This is the next milestone in showcasing the technology to make conversational social commerce possible,” Alforithmic’s COO Matt Lehmann told us. “There are still more than one flaws to iron out as well as tech challenges to overcome but overall we think this is a good way to show where this is moving to.”

In a blog post discussing how it recreated Einstein’s voice the startup writes about progress it made on one challenging element associated with the chatbot version — saying it was able to shrink the response time between turning around input text from the computational knowledge engine to its API being able to render a voiced response, down from an initial 12 seconds to less than three (which it dubs “near-real-time”). But it’s still enough of a lag to ensure the bot can’t escape from being a bit tedious.

Laws that protect people’s data and/or image, meanwhile, present a legal and/or ethical challenge to creating such “digital clones” of living humans — at least not without asking (and most likely paying) first.

Of course historical figures aren’t around to ask awkward questions about the ethics of their likeness being appropriated for selling stuff (if only the cloning technology itself, at this nascent stage). Though licensing rights may still apply — and do in fact in the case of Einstein.

“His rights lie with the Hebrew University of Jerusalem who is a partner in this project,” says Lehmann, before ‘fessing up to the artist licence element of the Einstein “voice cloning” performance. “In fact, we actually didn’t clone Einstein’s voice as such but found inspiration in original recordings as well as in movies. The voice actor who helped us modelling his voice is a huge admirer himself and his performance captivated the character Einstein very well, we thought.”

Turns out the truth about high-tech “lies” is itself a bit of a layer cake. But with deepfakes it’s not the sophistication of the technology that matters so much as the impact the content has — and that’s always going to depend upon context. And however well (or badly) the faking is done, how people respond to what they see and hear can shift the whole narrative — from a positive story (creative/educational synthesized media) to something deeply negative (alarming, misleading deepfakes).

Concern about the potential for deepfakes to become a tool for disinformation is rising, too, as the tech gets more sophisticated — helping to drive moves toward regulating AI in Europe, where the two main entities responsible for “Digital Einstein” are based.

Earlier this week a leaked draft of an incoming legislative proposal on pan-EU rules for “high risk” applications of artificial intelligence included some sections specifically targeted at deepfakes.

Under the plan, lawmakers look set to propose “harmonised transparency rules” for AI systems that are designed to interact with humans and those used to generate or manipulate image, audio or video content. So a future Digital Einstein chatbot (or sales pitch) is likely to need to unequivocally declare itself artificial before it starts faking it — to avoid the need for internet users to have to apply a virtual Voight-Kampff test.

For now, though, the erudite-sounding interactive Digital Einstein chatbot still has enough of a lag to give the game away. Its makers are also clearly labelling their creation in the hopes of selling their vision of AI-driven social commerce to other businesses.

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Epic Games buys photogrammetry software maker Capturing Reality

Epic Games is quickly becoming a more dominant force in gaming infrastructure M&A after a string of recent purchases made to bulk up their Unreal Engine developer suite. Today, the company announced that they’ve brought on the team from photogrammetry studio Capturing Reality to help the company improve how it handles 3D scans of environments and objects.

Terms of the deal weren’t disclosed.

Photogrammetry involves stitching together multiple photos or laser scans to create 3D models of objects that can subsequently be exported as singular files. As the computer vision techniques have evolved to minimize manual fine-tuning and adjustments, designers have been beginning to lean more heavily on photogrammetry to import real-world environments into their games. 

Using photogrammetry can help studio developers create photorealistic assets in a fraction of the time it would take to create a similar 3D asset from scratch. It can be used to quickly create 3D assets of everything from an item of clothing, to a car, to a mountain. Anything that exists in 3D space can be captured and as game consoles and GPUs grow more capable in terms of output, the level of detail that can be rendered increases as does the need to utilize more detailed 3D assets.

The Bratislava-based studio will continue operating independently even as its capabilities are integrated into Unreal. Epic announced some reductions to the pricing rates for Capturing Reality’s services, dropping the price of a perpetual license fee from nearly $18,000 to $3,750. In FAQs on the studio’s site, the company notes that they will continue to support nongaming use clients moving forward.

In 2019, Epic Games acquired Quixel, which hosted a library of photogrammetry “megascans” that developers could access.

 

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Adobe expands Acrobat Web, adds PDF text and image editing

For the longest time, Acrobat was Adobe’s flagship desktop app for working with — and especially editing — PDFs. In recent years, the company launched Acrobat on the web, but it was never quite as fully featured as the desktop version, and one capability a lot of users were looking for, editing text and images in PDFs, remained a desktop-only feature. That’s changing. With its latest update to Acrobat on the web, Adobe is bringing exactly this ability to its online service.

“[Acrobat Web] is strategically important to us because we have more and more people working in the browser,” Todd Gerber, Adobe’s VP for Document Cloud, told me. “Their day begins by logging into whether it’s G Suite or Microsoft Office 365. And so we want to be in all the surfaces where people are doing their work.” The team first launched the ability to create and convert PDFs, but as Gerber noted, it took a while to get to the point where being able to edit PDFs in a performant and real-time way was possible. “We could have done it earlier, but it wouldn’t have been up to the standards of being fast, nimble and quality.” He specifically noted that working with fonts was one of the more difficult problems the team faced in bringing this capability online.

He also noted that even though we tend to think of PDF as an Adobe format, it is an open standard and lots of third-party tools can create PDFs. That large ecosystem, with the potential for variations between implementations, also makes it more difficult to offer editing capabilities for Adobe.

With today’s launch, Adobe is also introducing a couple of additional browser-based features: protecting PDFs, splitting them into two and merging multiple PDFs. In addition, after working with Google last year to offer a handful of Acrobat shortcuts using the .new domain, Adobe is now launching a set of new shortcuts like EditPDF.new. The company plans to roll out more of these over the course of the next year.

In total, Adobe says, the company saw about 10 million clicks on its existing shortcuts, which just goes to show how many people try to convert or sign PDFs every day.

As Gerber noted, a lot of potential users don’t necessarily think of Acrobat first. Instead, what they want to do is compress a PDF or convert it. Acrobat Web and the .new domains help the company bring a new audience to the platform, he believes. “It’s unlocking a new audience for us that didn’t initially think of Adobe. They think about PDFs, they think about what they need to do with them,” he said. “So it’s allowing us to expand our customer base by being relevant in the way that they’re looking to discover and ultimately transact. Our journey with Acrobat web actually started with that notion: let’s go after the non-branded searches.”

Adobe, of course, funnels to the Acrobat desktop app all branded searches where users are explicitly looking for Acrobat, but for the more casual user, it brings them to Acrobat Web where they can easily perform whatever action they came for without even signing up for the service.

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Daily Crunch: India bans PUBG and other Chinese apps

India continues to crack down on Chinese apps, Microsoft launches a deepfake detector and Google offers a personalized news podcast. This is your Daily Crunch for September 2, 2020.

The big story: India bans PUBG and other Chinese apps

The Indian government continues its purge of apps created by or linked to Chinese companies. It already banned 59 Chinese apps back in June, including TikTok.

India’s IT Ministry justified the decision as “a targeted move to ensure safety, security, and sovereignty of Indian cyberspace.” The apps banned today include search engine Baidu, business collaboration suite WeChat Work, cloud storage service Tencent Weiyun and the game Rise of Kingdoms. But PUBG is the most popular, with more than 40 million monthly active users.

The tech giants

Microsoft launches a deepfake detector tool ahead of US election — The Video Authenticator tool will provide a confidence score that a given piece of media has been artificially manipulated.

Google’s personalized audio news feature, Your News Update, comes to Google Podcasts — That means you’ll be able to get a personalized podcast of the latest headlines.

Twitch launches Watch Parties to all creators worldwideTwitch is doubling down on becoming more than just a place for live-streamed gaming videos.

Startups, funding and venture capital

Indonesian insurtech startup PasarPolis gets $54 million Series B from investors including LeapFrog and SBI — The startup’s goal is to reach people who have never purchased insurance before with products like inexpensive “micro-policies” that cover broken device screens.

XRobotics is keeping the dream of pizza robots alive — XRobotics’ offering resembles an industrial 3D printer, in terms of size and form factor.

India’s online learning platform Unacademy raises $150 million at $1.45 billion valuation — India has a new startup unicorn.

Advice and analysis from Extra Crunch

The IPO parade continues as Wish files, Bumble targets an eventual debut — Alex Wilhelm looks at the latest IPO news, including Bumble planning to go public at a $6 to $8 billion valuation.

3 ways COVID-19 has affected the property investment market — COVID-19 has stirred up the long-settled dust on real estate investing.

Deep Science: Dog detectors, Mars mappers and AI-scrambling sweaters — Devin Coldewey kicks off a new feature in which he gets you all caught up on the most recent research papers and scientific discoveries.

(Reminder: Extra Crunch is our subscription membership program, which aims to democratize information about startups. You can sign up here.)

Everything else

‘The Mandalorian’ launches its second season on Oct. 30 — The show finished shooting its second season right before the pandemic shut down production everywhere.

GM, Ford wrap up ventilator production and shift back to auto business — Both automakers said they’d completed their contracts with the Department of Health and Human Services.

The Daily Crunch is TechCrunch’s roundup of our biggest and most important stories. If you’d like to get this delivered to your inbox every day at around 3pm Pacific, you can subscribe here.

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Engineers can now reverse-engineer 3D models

A system that uses a technique called constructive solid geometry (CSG) is allowing MIT researchers to deconstruct objects and turn them into 3D models, thereby allowing them to reverse-engineer complex things.

The system appeared in a paper entitled “InverseCSG: Automatic Conversion of 3D Models to CSG Trees” by Tao Du, Jeevana Priya Inala, Yewen Pu, Andrew Spielberg, Adriana Schulz, Daniela Rus, Armando Solar-Lezama, and Wojciech Matusik.

“At a high level, the problem is reverse engineering a triangle mesh into a simple tree. Ideally, if you want to customize an object, it would be best to have access to the original shapes — what their dimensions are and how they’re combined. But once you combine everything into a triangle mesh, you have nothing but a list of triangles to work with, and that information is lost,” said Tao Du to 3DPrintingIndustry. “Once we recover the metadata, it’s easier for other people to modify designs.”

The process cuts objects into simple solids that can then be added together to create complex objects. Because 3D scanning is imperfect, the creation of mesh models of various objects rarely leads to a perfect copy of the original. Using this technique, individual parts are cut away, analyzed and reassembled, allowing for a more precise scan.

“Further, we demonstrated the robustness of our algorithm by solving examples not describable by our grammar. Finally, since our method returns parameterized CSG programs, it provides a powerful means for end-users to edit and understand the structure of 3D meshes,” said Du.

The system detects primitive shapes and then modifies them. This allows it to recreate almost any object with far better accuracy than in previous versions of the software. It’s a surprisingly cool way to begin hacking hardware in order to understand it’s shape, volume and stability.

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