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NVIDIA GTC San Jose 2017

S7312 - ADAS Computer Vision and Augmented Reality Solution

Session Speakers
Session Description

We'll address how next-generation informational ADAS experiences are created by combining machine learning, computer vision, and real-time signal processing with GPU computing. Computer vision and augmented reality (CVNAR) is a real-time software solution, which encompasses a set of advanced algorithms that create mixed augmented reality for the driver by utilizing vehicle sensors, map data, telematics, and navigation guidance. The broad range of features includes augmented navigation, visualization, driver infographics, driver health monitoring, lane keeping, advanced parking assistance, adaptive cruise control, and autonomous driving. Our approach augments drivers' visual reality with supplementary objects in real time, and works with various output devices such as head unit displays, digital clusters, and head-up displays.

 

Additional Session Information
Intermediate
Talk
Computer Vision and Machine Vision, Self-Driving Cars, AI for In-Vehicle Applications
Automotive
25 minutes
Session Schedule