The company’s labeled training data will enable automobile manufacturers to build computer vision systems to meet new driver safety regulatory requirements.
SAN FRANCISCO, July 27, 2021 /PRNewswire/ — Synthesis AI, a pioneer in synthetic data technologies, today announced enhanced capabilities to simulate driver behavior in the car cabin environment to ensure Automobile and Autonomous Vehicle (AV) manufacturers have access to high-quality, perfectly labeled training data to build driver safety systems. Through the company’s synthetic data-as-a-service FaceAPI solution, manufacturers can now test intelligent sensing configurations and driver safety monitoring systems across a broader set of environments and solutions without compromising customer privacy.
“For safe and general deployment of automobiles, especially AVs, Artificial Intelligence (AI) systems need to perceive the world reliably and make proper decisions across a wide range of situations,” said Yashar Behzadi, CEO of Synthesis AI. “With recent attention directed to driver monitoring systems to improve road safety, it’s inevitable that the demand for synthetic data and its simulation capabilities will only increase, as the technology is uniquely positioned to accelerate the development of driver safety and autonomous systems.”
Beginning in 2022, all new cars entering the EU market must be equipped with advanced safety systems. Among the mandatory safety measures is distraction recognition and alert systems on trucks and buses to warn when vulnerable road users, such as pedestrians or cyclists, are in close proximity.
To meet the new requirements, automobile companies will be faced with spending vast amounts of resources building and deploying cars to collect diverse datasets to train AI models. However, it is both costly and impractical to capture sufficient examples of diverse sets of drivers across a wide variety of situations. Synthetic data will play an increasingly important role in overcoming these bottlenecks.
Manufacturers will have the ability to mimic driver behavior in virtual car environments to test and iterate their models across a broader set of settings and situations without building and deploying fleets of vehicles. To meet the data demands of the in-cabin driver safety monitoring systems, Synthesis AI’s FaceAPI enables the on-demand generation of thousands of unique identities with granular control of emotion, gaze angle, head pose, accessories, environments, camera systems (e.g., RGB, NIR, TOF), and more. Since the data is generated, the image data comes with an expanded set of pixel-perfect labels, including facial landmarks, gaze, angle, depth maps, segmentation, surface normals, and facial meshes. As a result, automotive manufacturers will be able to build more robust training models in a fraction of the time and cost of traditional human-annotated real-world data approaches.
“The new EU regulations demonstrate the growing expectation for car manufacturers to have a comprehensive understanding of all the human variables that can impact road safety. Synthetic data will play an instrumental role in meeting this need,” said Dr. Rana el Kaliouby, Deputy CEO of Smart Eye, and former Co-Founder and CEO of Affectiva. “Our collaboration with Synthesis AI has allowed us to test our computer vision models with large sets of diverse data that are indicative of real-world use-cases. As a result, we’re able to deliver advanced driver monitoring and Interior Sensing systems that meet the requirements of automakers today and in the future.”
Synthesis AI, which works with automobile and autonomous vehicle manufacturers and tier-1 suppliers, is continually building capability to meet the future demands of manufacturers.
To learn more about the use of synthetic data to improve state-of-the-art facial models, download the white paper, Synthetic Data Case Studies: It Just Works.
About Synthesis AI
Synthesis AI, a San Francisco-based technology company, is pioneering the use of synthetic data to build more capable computer vision models. Through a proprietary combination of generative neural network and cinematic CGI pipelines, Synthesis’ platform can programmatically create vast amounts of perfectly-labeled image data at orders of magnitude increased speed and reduced cost compared to current approaches.
SOURCE Synthesis AI