Artificial Intelligence | News | Insights | AiThority
[bsfp-cryptocurrency style=”widget-18″ align=”marquee” columns=”6″ coins=”selected” coins-count=”6″ coins-selected=”BTC,ETH,XRP,LTC,EOS,ADA,XLM,NEO,LTC,EOS,XEM,DASH,USDT,BNB,QTUM,XVG,ONT,ZEC,STEEM” currency=”USD” title=”Cryptocurrency Widget” show_title=”0″ icon=”” scheme=”light” bs-show-desktop=”1″ bs-show-tablet=”1″ bs-show-phone=”1″ custom-css-class=”” custom-id=”” css=”.vc_custom_1523079266073{margin-bottom: 0px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”]

Nexar Announces AI-Powered Image Retrieval Method for Better Localization in Cities

By Leveraging Billions of Images in Its Network, Nexar Offers a Scalable Solution for Navigation & Autonomous Vehicle Applications

Related Posts
1 of 39,905

Nexar is announcing a scalable method that greatly improves GPS location accuracy in urban areas. The mobility company is showcasing its innovative approach today at the Computer Vision and Pattern Recognition Conference (CVPR), the premier annual computer vision event.

As a benchmark to evaluate this new visual localization approach, Nexar is also releasing a dataset and benchmark based on anonymized dash cam and GPS information from its connected vehicle network to advance the research of visual localization for safety applications.

By pairing Nexar-powered dash cameras with the Nexar app, drivers join the company’s global safe-driving network, where every vehicle is alerted to what’s happening on the road ahead with the help of other vehicles around it. Collisions, traffic, closed lanes, dangerous road conditions ahead – it’s a virtuous cycle of information sharing aimed at eliminating collisions worldwide.

Read More: Lockheed Martin and Drone Racing League Announce 2019 AlphaPilot Teams

In order to deliver these critical alerts, Nexar needs an efficient and accurate way of knowing in real-time exactly where vehicles are on the road. In dense urban environments, GPS is highly inaccurate as satellite signals are often blocked or reflected by high-rise buildings (urban canyons). This poses a critical challenge for vehicle-to-vehicle (v2v) safety applications. Nexar’s new AI-powered image retrieval algorithm will dramatically improve localization in cities, solving a problem that has long-plagued both rideshare operators and navigation apps, as well as autonomous vehicle manufacturers. Nexar’s research of crowd-sourced data of over 250,000 driving hours in New York City found that at least 40% of rides suffered GPS errors of 10 meters or more due to the urban canyon effect.

Nexar’s method for localization is based on its continuously growing database of fresh road imagery observed by its network. Currently, at over 10 billion new road images indexed per month, Nexar’s network provides unparalleled depth and freshness. Nexar’s method solves for the challenges presented by other mapping companies, such as Google, which can use a vast Street View image repository, but lack the minute-level freshness that Nexar provides.

Read More: AI Venture Builder to Raise $2.5 Million to Launch AI Companies

Technically speaking, to solve for the failings of satellite GPS, Nexar has developed a hybrid coarse-to-fine approach that leverages visual and GPS location cues. Lead by Nexar’s Director of Artificial Intelligence Research Dr. Ilan Kadar and Chief Scientist Prof. Trevor Darrell, the company has trained a deep learning model to identify a driver’s accurate location using its massive archive of anonymized images. The archive includes billions of these images from more than 400 million miles driven on the Nexar network.

Nexar’s experiments confirm that this localization approach is highly effective in challenging urban environments, reducing the distribution of localization errors by an order of magnitude. This method will be used to deliver alerts to Nexar users, including dangerous intersections and collisions on the road ahead.

“This new localisation method makes it possible for Nexar to deliver on our founding promise, which is to help rid the world of collisions,” says Nexar co-founder and Chief Technology Officer Bruno Fernandez-Ruiz. “And the benefits will go far beyond our network – this approach could one day allow autonomous vehicles to reliably navigate cities. It’s just as accurate and far less expensive than structure-based techniques such as lidar, which are limited in scale and expensive to compute. So the potential is really tremendous.”

Read More: IBM AI and Cloud Technology Helps Agriculture Industry Improve the World’s Food and Crop Supply

  1. köylü kızın sikişi says

    Seçim Anne, Büyük Memeler, Amatör, Göt, Sakso, Amerikalı, HD, Anal, Sarışın, Olgun, Büyük
    Göt, Büyük Yarrak, Genç Erkek Avcısı Yaşlı Kadın, Evde.

  2. Hurrah, that’s what I was seeking for, what a data! present here at this
    website, thanks admin of this website.

  3. I enjoy reading an article that can make men and women think.
    Also, many thanks for allowing me to comment!

  4. Hmm it seems like your website ate my first comment (it was
    extremely long) so I guess I’ll just sum it up what I wrote and say,
    I’m thoroughly enjoying your blog. I as well am an aspiring blog writer but I’m still
    new to the whole thing. Do you have any helpful hints
    for novice blog writers? I’d genuinely appreciate it.

  5. Good day! This is kind of off topic but I need some guidance from an established blog.
    Is it very difficult to set up your own blog? I’m not very techincal but I can figure
    things out pretty fast. I’m thinking about making my own but I’m not sure
    where to begin. Do you have any ideas or suggestions?
    Appreciate it

  6. Scrap Copper trading says

    Scrap Copper recycling Copper waste purchaser Metal waste reclamation facility
    Copper cable recycling solutions, Metal waste, Copper scrap volume estimation

  7. Copper scrap says

    Copper recycling center Copper scrap reclaiming Scrap metal reclaim
    Copper cable scrap analysis, Scrap metal export regulations, Copper reclamation services

Leave A Reply

Your email address will not be published.