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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

Chery, one of China’s leading automakers, is adopting the new ZF ProAI system, powered by NVIDIA DRIVE AI self-driving technology, to bring Level 3 autonomous driving to the world’s biggest auto market.

The news was announced today at the North American International Auto Show, in Detroit, by Konstantin Sauer, CEO of ZF, one of the world’s biggest auto parts suppliers.

Chery road testing its intelligent interconnected cars.

Chery, which makes cars, minivans and SUVs, will be the first Chinese carmaker to adopt the new ZF ProAI system, developed by NVIDIA, Baidu and ZF.

For over two decades, Chery has been making vehicles for the Chinese market, as well as for more than 80 countries globally. The company has earned a reputation for bringing advanced technologies to its highly affordable, entry-level models.

“This collaboration will democratize autonomous driving functions in one of the most important automotive markets of the world and bring autonomous driving for everyone,” said Sauer.

At CES 2018 last week, NVIDIA founder and CEO Jensen Huang highlighted our partnership with Baidu and ZF to move autonomous vehicles from development into production. Together, the companies are pioneering advances in deep learning and AI to create the first AI autonomous vehicle computing platform for China.

A Trifecta of Automotive Technology

Powering the ZF ProAI is the NVIDIA DRIVE Xavier AI car computer. Xavier is the world’s most complex and advanced SoC, capable of performing 30 deep learning TOPS (trillions of operations per second), using only 30 watts of power.

NVIDIA DRIVE Xavier cranks through 30 TOPS at just 30 watts.

ZF, a leader in automotive safety, brings expertise for system integration of the car computer and sensors. ZF ProAI will process inputs from multiple cameras, plus lidar and radar, paint a 360-degree view around the vehicle, locate it on an HD map, and find a safe path through traffic.

Baidu’s Apollo open autonomous driving platform provides a comprehensive, secure and reliable all-in-one solution that supports all major features and functions of an autonomous vehicle.

To learn more, check out ZF’s press release from NAIAS 2018.

 

 

The post Chinese Automaker Chery to Use NVIDIA-Powered ZF ProAI for Level 3 Autonomous Cars appeared first on The Official NVIDIA Blog.

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.