US Patent Application 18144651. USING GESTURES TO CONTROL MACHINES FOR AUTONOMOUS SYSTEMS AND APPLICATIONS simplified abstract

USING GESTURES TO CONTROL MACHINES FOR AUTONOMOUS SYSTEMS AND APPLICATIONS

Organization Name

NVIDIA Corporation

Inventor(s)

Anshul Jain of Santa Clara CA (US)

Ratin Kumar of Cupertino CA (US)

Feng Hu of Santa Clara CA (US)

Niranjan Avadhanam of Santa Clara CA (US)

Atousa Torabi of Santa Clara CA (US)

Hairong Jiang of Campbell CA (US)

Ram Ganapathi of San Jose CA (US)

Taek Kim of San Jose CA (US)

USING GESTURES TO CONTROL MACHINES FOR AUTONOMOUS SYSTEMS AND APPLICATIONS - A simplified explanation of the abstract

This abstract first appeared for US patent application 18144651 titled 'USING GESTURES TO CONTROL MACHINES FOR AUTONOMOUS SYSTEMS AND APPLICATIONS

Simplified Explanation

- The patent application describes an advanced AI-assisted vehicle system that uses a range of sensors to collect data inside and outside the vehicle. - The system utilizes neural networks to perform various functions such as facial recognition, eye tracking, gesture recognition, and head position tracking to monitor the condition and safety of the driver and passengers. - The system can also track the body pose and signals of people both inside and outside the vehicle to understand their intentions and actions. - By tracking the driver's gaze, the system can identify objects that the driver may not see, such as cross-traffic and approaching cyclists. - The system can provide notifications, advice, and warnings about potential hazards. - It can also take corrective action by controlling different vehicle subsystems or even autonomously controlling the entire vehicle if necessary. - The system can work with existing vehicle systems to provide enhanced analytics and recommendations.

Original Abstract Submitted

Approaches for an advanced AI-assisted vehicle can utilize an extensive suite of sensors inside and outside the vehicle, providing information to a computing platform running one or more neural networks. The neural networks can perform functions such as facial recognition, eye tracking, gesture recognition, head position, and gaze tracking to monitor the condition and safety of the driver and passengers. The system also identifies and tracks body pose and signals of people inside and outside the vehicle to understand their intent and actions. The system can track driver gaze to identify objects the driver might not see, such as cross-traffic and approaching cyclists. The system can provide notification of potential hazards, advice, and warnings. The system can also take corrective action, which may include controlling one or more vehicle subsystems, or when necessary, autonomously controlling the entire vehicle. The system can work with vehicle systems for enhanced analytics and recommendations.