TOCA Social chooses Deepen AI’s calibration suite for targetless camera calibration

November 7, 2022
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24th October 2022: Santa Clara, CA - Deepen AI, a world leader in calibration tools for multi-sensor systems, today announced their partnership with TOCA Social. TOCA Social is the world’s first interactive football and dining experience, combining immersive gaming and world-class food and drink.

Deepen Calibrate makes the critical task of sensor data calibration simple and quick. Deepen Calibrate manages the complexities of the calibration process, ensuring accuracy and making autonomous systems safer, while also doing a job that typically requires the time of a Ph.D-level engineer into something anyone can do.

TOCA Social brings together interactive football, delicious food, and five-star cocktails. In collaboration with TOCA Social, Deepen has successfully deployed Deepen Calibrate to bring down calibration effort by almost 85%, leading to lower human resources and increasing cost-effectiveness.

“By using Deepen Calibrate, TOCA is able to save hundreds in man hours which has significantly reduced the downtime for our sensors. The data visualization makes it very powerful, allowing us to instantly review the result and take action accordingly. We look forward to working closely with Deepen AI and further enhancing our calibration capabilities with them. ” -  Dr. Conrad Spiteri, Global Head of Technology, TOCA Social

Sensor data calibration is critical for all vision and autonomous systems. These systems depend on sets of sensors, including cameras and LiDAR, to “see” the world around them, but these sensors must be carefully calibrated with each other and with reality to ensure the systems work properly and safely. Until now, sensor calibration has been the kind of task that mixed art and science and required the time of the most senior and experienced engineers on any team.  

Deepen Calibrate is aimed at enabling users to automate, visualize and inspect data quality integrity for training and validation. Deepen Calibrate can cut the time spent on calibrating multi-sensor data from hours to minutes, massively accelerating computer vision training -- and opening the world for more AI technology by democratizing this key part of data curation.

Key features of Deepen Calibrate include:

  • Automate most of the offices utilizing targetless calibration
  • Visualize & inspect integrity of multi-sensor data seamlessly
  • Calculate intrinsic & extrinsic calibration parameters
  • Export calibrated multi-sensor data into Deepen’s annotation tools

“With Deepen Calibrate, we empower our customers to automate, visualize and inspect calibration data with an API-- while also saving them engineering man-hours -- so they can move ahead with their computer vision training datasets with confidence. Our tool can be easily customized to meet all sensor calibration requirements”  said Mohammad Musa, CEO & Co-founder of Deepen AI.

Deepen Calibrate offers a wide range of calibration products supporting different kinds of sensors like Camera, LiDAR, Radar, IMU, and more. Deepen Calibrate extends the company’s suite of data lifecycle tools, Deepen Annotate and engineering success. 

Licensing and customized packages are available to enterprises. You can reach the Deepen team at info@deepen.ai or visit www.deepen.ai/calibrate

About Deepen

Deepen AI is a Silicon Valley-based start-up and the only safety-first data lifecycle tools and services company focused on machine learning and AI for autonomous systems. With tools and services that are customizable to suit the needs of enterprises as well as start-ups they have happy customers of every size across the globe. Visit Deepen.ai for more information.

About TOCA

TOCA Social is the new entertainment concept transforming how we meet and play. Built around accessible and interactive football-based games, our stylish venues give players of all kinds a place to come together and put their name in lights. With live events, a menu to wow and an array of world-class cocktails, football’s never looked so good.

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