Nvidia corporation (20240104941). SENSOR CALIBRATION USING FIDUCIAL MARKERS FOR IN-CABIN MONITORING SYSTEMS AND APPLICATIONS simplified abstract

SENSOR CALIBRATION USING FIDUCIAL MARKERS FOR IN-CABIN MONITORING SYSTEMS AND APPLICATIONS

Organization Name

nvidia corporation

Inventor(s)

Yuzhuo Ren of Sunnyvale CA (US)

Hairong Jiang of Campbell CA (US)

Niranjan Avadhanam of Saratoga CA (US)

Varsha Chandrashekhar Hedau of Sunnyvale CA (US)

SENSOR CALIBRATION USING FIDUCIAL MARKERS FOR IN-CABIN MONITORING SYSTEMS AND APPLICATIONS - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240104941 titled 'SENSOR CALIBRATION USING FIDUCIAL MARKERS FOR IN-CABIN MONITORING SYSTEMS AND APPLICATIONS

Simplified Explanation

The abstract describes sensor parameter calibration techniques for in-cabin monitoring systems, specifically focusing on an occupant monitoring system within a vehicle or machine cabin. Here are some key points to explain the patent/innovation:

• Sensor parameter calibration techniques for in-cabin monitoring systems
• Real-time assessments of driver and occupant presence, gaze, alertness, and other conditions
• Calibration parameter determination for an interior image sensor to reference 2D captured images to an in-cabin 3D coordinate system
• Detection of fiducial points in an interior space image, determination of 2D and 3D coordinates, and calibration parameter configuration based on rotation-translation transform

1. 1. 1. Potential Applications

- Automotive industry for driver monitoring systems - Industrial machinery for operator safety and performance monitoring

1. 1. 1. Problems Solved

- Accurate real-time assessment of driver and occupant conditions - Improved safety measures within vehicles and machinery

1. 1. 1. Benefits

- Enhanced driver and occupant safety - Real-time monitoring for timely interventions - Improved overall performance and efficiency

1. 1. 1. Potential Commercial Applications
         1. Enhancing In-Cabin Monitoring Systems for Automotive Safety

1. 1. 1. Possible Prior Art

No known prior art.

1. 1. 1. Unanswered Questions
         1. How does this calibration technique compare to existing methods in terms of accuracy and efficiency?

The article does not provide a direct comparison with existing calibration methods.

1. 1. 1. 1. Are there any limitations or challenges in implementing this calibration technique in different types of vehicles or machinery?

The article does not address potential limitations or challenges in implementation across various platforms.

Original Abstract Submitted

in various examples, sensor parameter calibration techniques for in-cabin monitoring systems and applications are presented. an occupant monitoring system (oms) is an example of a system that may be used within a vehicle or machine cabin to perform real-time assessments of driver and occupant presence, gaze, alertness, and/or other conditions. in some embodiments, a calibration parameter for an interior image sensor is determined so that the coordinates of features detected in 2d captured images may be referenced to an in-cabin 3d coordinate system. in some embodiments, a processing unit may detect fiducial points using an image of an interior space captured by a sensor, determine a 2d image coordinate for a fiducial point using the image, determine a 3d coordinate for the fiducial point, determine a calibration parameter comprising a rotation-translation transform from the 2d image coordinate and the 3d coordinate, and configure an operation based on the calibration parameter.