Tesla, inc. (20240185445). ARTIFICIAL INTELLIGENCE MODELING TECHNIQUES FOR VISION-BASED OCCUPANCY DETERMINATION simplified abstract
ARTIFICIAL INTELLIGENCE MODELING TECHNIQUES FOR VISION-BASED OCCUPANCY DETERMINATION
Organization Name
Inventor(s)
Pengfei Phil Duan of Austin TX (US)
Nishant Desai of Austin TX (US)
Ashok Elluswamy of Austin TX (US)
ARTIFICIAL INTELLIGENCE MODELING TECHNIQUES FOR VISION-BASED OCCUPANCY DETERMINATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240185445 titled 'ARTIFICIAL INTELLIGENCE MODELING TECHNIQUES FOR VISION-BASED OCCUPANCY DETERMINATION
Simplified Explanation
The patent application describes methods and systems for using artificial intelligence modeling techniques to analyze camera feed received from an ego object to generate occupancy data indicating whether different voxels within the ego's surroundings are occupied by an object having mass.
- The method involves inputting image data of a space around the ego object into an artificial intelligence model, predicting the occupancy attribute of a plurality of voxels, and generating a dataset based on the voxels and their corresponding occupancy attribute.
Potential Applications:
- Surveillance systems
- Robotics navigation systems
Problems Solved:
- Efficient object detection in a given space
- Real-time monitoring of occupancy in a specific area
Benefits:
- Improved security measures
- Enhanced automation processes
Potential Commercial Applications of this Technology: Optimizing Retail Store Layouts for Customer Flow
Possible Prior Art: One possible prior art could be the use of traditional computer vision techniques for object detection and tracking in a given space.
Unanswered Questions: 1. How does the artificial intelligence model handle occlusions in the camera feed? 2. What is the accuracy rate of the occupancy data generated by the system?
Original Abstract Submitted
disclosed herein are methods and systems for using artificial intelligence modeling techniques to train and execute an artificial intelligence model to analyze camera feed received from an ego to generate an occupancy data indicating whether different voxels within the ego's surroundings are occupied by an object having mass. a method comprises inputting, using a camera of an ego object, image data of a space around the ego object into an artificial intelligence model; predicting, by executing the artificial intelligence model, an occupancy attribute of a plurality of voxels; and generating a dataset based on the plurality of voxels and their corresponding occupancy attribute.
