Abstract: In various examples, calibration techniques for interior depth sensors and image sensors for in-cabin monitoring systems and applications are provided. An intermediary coordinate system may be generated using calibration targets distributed within an interior space to reference 3D positions of features detected by both depth-perception and optical image sensors. Rotation-translation transforms may be determined to compute a first transform (H1) between the depth-perception sensor's 3D coordinate system and the 3D intermediary coordinate system, and a second transform (H2) between the optical image sensor's 2D coordinate system and the intermediary coordinate system. A third transform (H3) between the depth-perception sensor's 3D coordinate system and the optical image sensor's 2D coordinate system can be computed as a function of H1 and H2. The calibration targets may comprise a structural substrate that includes one or more fiducial point markers and one or more motion targets.

Abstract: 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.

Abstract: An image into which one or more objects are to be inserted is obtained. Based on the image, both a 3-dimensional (3D) representation and a light model of the scene in the image are generated. One or more objects are added to the 3D representation of the scene. The 3D representation of the scene is rendered, based on the light model, to generate a modified image that is the obtained image modified to include the one or more objects.

Abstract: An image into which one or more objects are to be inserted is obtained. Based on the image, both a 3-dimensional (3D) representation and a light model of the scene in the image are generated. One or more objects are added to the 3D representation of the scene. The 3D representation of the scene is rendered, based on the light model, to generate a modified image that is the obtained image modified to include the one or more objects.