公开(公告)号：US20250022289A1

公开(公告)日：2025-01-16

申请号：US18349827

申请日：2023-07-10

Applicant: NVIDIA Corporation

Inventor： Sakthivel SIVARAMAN ,  Rajath SHETTY ,  Hairong JIANG ,  Arjun GURU ,  Yuzhuo REN

IPC: G06V20/59 ,  G06T7/50 ,  G06V40/10

Abstract: In various examples, occupant assessment using multi-modal sensor fusion for monitoring systems and applications are provided. In some embodiments, an occupant monitoring system comprises an occupant evaluation function that may predict at least one characteristic representative of a size of the occupant. The occupant evaluation function may include a first processing path that generates a representation of features corresponding to the occupant based on optical image data, and a second processing path that performs operations to determine a depth corresponding to the one or more features based on depth data derived from the optical image data and the point cloud depth data. In some embodiments, a three-dimensional pose detection model generates a three-dimensional pose estimate of the occupant using the optical image data, and the three-dimensional pose estimate is scaled to an absolute pose based on the point cloud depth data.

公开(公告)号：US20250022288A1

公开(公告)日：2025-01-16

申请号：US18219969

申请日：2023-07-10

Applicant: NVIDIA Corporation

Inventor： Sakthivel SIVARAMAN ,  Arjun GURU ,  Rajath SHETTY ,  Shagan SAH ,  Varsha HEDAU

IPC: G06V20/59 ,  G06V10/82 ,  G06V40/16

Abstract: In various examples, sensor data (e.g., image and/or RADAR data) may be used to detect occupants and classify them (e.g., as children or adults) using one or more predictions that represent estimated age (e.g., based on detected limb length, a detected face) and/or detected child presence (e.g., based on detecting an occupied child seat). In some embodiments, multiple predictions generated using multiple machine learning models (and optionally one or more corresponding confidence values) may be combined using a state machine and/or one or more machine learning models to generate a combined assessment of occupant presence and/or age for each occupant and/or supported occupant slot. As such, the techniques described herein may be utilized to detect child presence, detect unattended child presence, determine age or size of a particular occupant, and/or take some responsive action (e.g., trigger an alarm, control temperature, unlock door(s), permit or disable airbag deployment, etc.).