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We’re fortunate enough to have another fine 3D video from New Media Film Festival to share with you here on 3DVisionLive—a pop music video from Italy called “The Way,” which you can view here. Even better, New Media Film Festival has provided an interview with one of the co-directors of the video, Edoardo Ballanti, which provides insights on how the video was created and the vision behind it. Enjoy! (Alice Corsi also co-directed the video.) What was the Inspiration behind “...
The Fall Photo Contest received nearly 100 images – thanks to all that entered! The contest called for your best “nature” shots with the only other requirement being that they had to be true stereo images. Submissions ranged from shots of spiders in gardens to artistic approaches to tasteful nudes. As before, members were invited to vote for the winner by tagging images in the contest gallery as favorites. Without further ado, the winner is: Autumn Goodbye to Summer This...
In driver 334.89 NVIDIA introduced a new proprietary rendering mode for 3D Vision that enables us to improve the 3D experience for many key DirectX 10 and 11 games. This mode is now called “3D Compatibility Mode”. We have continued to iterate on this feature in beta driver 337, increasing game support and adding a toggle key to enable/disable the mode. Games with 3D Compatibility Mode will launch in this mode by default. To change the render mode back to standard 3D Vision...
3DVisionLive’s first-ever short-form 3D video contest received 14 entries that showed a great deal of diversity, ranging from video game captures to commercial-style clips to raw captures of pets or people doing cool things (such as bashing each other with swords). During judging we laughed, we cried (okay, maybe not), and we simply scratched our heads…. But seriously: thank-you to all that participated and we hope to see more of your content uploaded to the site for all to...
The submission period for the Fall Photo Contest is now closed, and we are happy to report we’ve received nearly 100 images from our members for consideration. And, once again, we’re opening the judging process to our community as well to help us determine the winners. The full gallery of images may be seen by clicking the link above. Between now and February 10th (11:59 PST), please view all of the images in the gallery and place your votes for the ones you’d like to win by...

Recent Blog Entries

Amir Hever was driving into a government facility a few years ago when he discovered a huge flaw in their security process. As he approached the entrance gate, a security guard dropped to his knees to look underneath his vehicle.

“When he stood up, I asked him what he was looking for,” said Hever, CEO and co-founder of computer vision startup UVeye. “The security guard answered honestly that he was looking for threats but actually couldn’t see anything. That’s when I realized that something wasn’t working right.”

Hever assembled a team, and began researching the problem and potential solutions. Thus was born in 2016 UVeye, which has since built an under-vehicle inspection system that uses deep learning to bridge the security gap.

Much of the New York-based company’s work centered on grasping the vast variety of vehicle undercarriages, not to mention the changes they undergo after thousands of miles on the road. What Hever and his team learned that it’s not easy to identifying anomalies in vehicle undercarriages.

“We didn’t know what we’re looking for as there is no standard of what a threat would look like in the undercarriage,” said Hever. “Moreover, threats are usually concealed.”

More Than Schematics Needed

UVeye quickly learned that schematics provided by vehicle manufacturers aren’t enough because, after thousands of miles of road time, undercarriages don’t look like they did when they came off the assembly line. The answer was to develop an algorithm for unsupervised learning that would make it possible to spot threats — no matter how well concealed or the condition of the vehicle’s undercarriage.

The company rented hundreds of vehicles in various conditions and scanned their undercarriages, generating both 2D images and 3D models. That data was fed into its deep learning model, which maps the location of all the parts (segmentation) and then analyzes each segment separately and looks for anomalies.

This allows it to detect any alterations or anomalies to those parts, or the presence of foreign objects as small as USB drives. It can also tell whether a chunk of snow or mud looks natural, or if it might be a disguise used to conceal something.

UVeye uses workstations running multiple NVIDIA GeForce GTX 1080 GPUs to train its models. It turns to cloud-based GPUs running on Amazon Web Services or Microsoft Azure to train beyond its workstations’ capabilities, or to speed up the process further.

Hever said the use of GPUs, as well as the CUDA parallel computing model, significantly sped up the company’s training and development processes, as well as the system’s ability to generate results.

UVeye’s first line of products enables customers to automatically scan, detect and identify anomalies, modifications or foreign objects in the undercarriage of any vehicle. The company has already installed its system — packaged as a piece of hardware that sits in the ground, scanning vehicles that pass over it — at more than 30 sites worldwide. This has provided abundant test data verifying the system’s effectiveness.

“Our machine learning algorithm detects anomalies in any vehicle whilst in motion, within three seconds,” said Hever. “GPUs are making it possible.”

Inspection as a Service

Today, UVeye is revolutionizing vehicle inspection for the automotive industry. Additional applications for its system focus on security, with homeland security representing a robust market for the company’s technology.

“The need for an automatic external inspection system for vehicles that can detect anomalies, changes and dents, and also track changes over time, is huge,” Hever said.

The company has also leveraged its algorithms to analyze other parts of vehicles besides undercarriages and to inspect any vehicle from all sides.

“UVeye’s 360-degree system can detect vehicle leaks, wear and tear, and a wide variety of mechanical problems or damages,” Hever said.

From auto sales and rentals to fleet management and maintenance, Hever sees infinite opportunities for his company’s Inspection-as-a-Service model to ensure safe and reliable operation of vehicles.

Said Hever, “We are going to change the way that people and organizations inspect their cars.”

The post Computer Vision Startup Plugs Critical Security Hole in Vehicle Inspection appeared first on The Official NVIDIA Blog.

There was no escaping the automotive innovations, or the camera-toting crowds gawking at them, at CES 2018 this week in Las Vegas.

NVIDIA kicked off the show with a torrent of new partnerships and autonomous driving solutions. Uber, Volkswagen, Aurora, ZF, Baidu and Mercedes-Benz all announced new initiatives with NVIDIA. The announcements brought the total number of partners developing on the NVIDIA DRIVE platform to more than 320.

Around the North Hall, attendees at the world’s largest trade show could find our partners at almost every turn. Starting at the NVIDIA booth, Roborace drew crowds — and U.S. Secretary of Transportation Elaine Chao — with the CES debut of its low-set, sinuous Robocar. The NVIDIA-powered electric race car will take part in a future autonomous series, sanctioned by Formula E.

Nearby in the NVIDIA Holodeck, visitors took a virtual bus trip through time. After donning head-mounted displays they got to experience the transformation of the iconic 1960s era Volkswagen Type 2 microbus into the AI-infused, all-electric VW I.D. Buzz slated for 2022. Holodeck is a VR lab that lets far-flung teams come together in a realistic virtual environment to interact with photorealistic models of their designs.

For attendees interested in seeing self-driving go big in the most literal sense, TuSimple displayed an autonomous Peterbilt truck with NVIDIA DRIVE technology. The company provides a camera- and radar-based technology for autonomous driving. The startup expects to begin commercial operation of their level 4 system — supervised by test drivers — this year.

While NVIDIA has worked with both ZF and Baidu for over a year, a new initiative announced at CES brings the three companies together to realize a commercial solution for autonomous valet parking this year, with production vehicles using AI self-driving technologies expected on the roads of China starting in 2020.

Amid stunning visuals at the Mercedes-Benz booth, the automaker unveiled the NVIDIA-powered MBUX infotainment system. This revolutionary in-cabin experience can learn and adapt to driver and passenger preferences, thanks to artificial intelligence.

Dozens of other NVIDIA DRIVE partners attended the event to share their latest work with the crowds who descended on Las Vegas for the week. We spent time with many of them on the show floor, including Tertavue, Expolorer.ai, Cepton, Navya, HERE, AutonomouStuff, Deepmap, Innoviz, Cognata, Adasky and Torc. Watch our partner recap video above to hear about the latest self-driving innovations.

Take an even deeper dive into the technology at the heart of the autonomous vehicle revolution. Join us in March for the GPU Technology Conference in Silicon Valley.

The post Automotive Innovations Powered by NVIDIA DRIVE Draw Crowds at CES 2018 appeared first on The Official NVIDIA Blog.