View source for Tesla, inc. (20240125934). ANNOTATION CROSS-LABELING FOR AUTONOMOUS CONTROL SYSTEMS simplified abstract

=ANNOTATION CROSS-LABELING FOR AUTONOMOUS CONTROL SYSTEMS=


==Organization Name==

[[:Category:tesla, inc.|tesla, inc.]]


[[Category:tesla, inc.]]

==Inventor(s)==

[[:Category:Anting Shen of Berkeley CA (US)|Anting Shen of Berkeley CA (US)]][[Category:Anting Shen of Berkeley CA (US)]]

==ANNOTATION CROSS-LABELING FOR AUTONOMOUS CONTROL SYSTEMS - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240125934 titled 'ANNOTATION CROSS-LABELING FOR AUTONOMOUS CONTROL SYSTEMS

==Simplified Explanation==

The abstract describes an annotation system that uses annotations from sensor measurements to identify the location of a characteristic object in a three-dimensional space.

* The system uses annotations from a first set of sensor measurements to identify the location of a characteristic object in a two-dimensional space.
* It then determines a spatial region in the three-dimensional space of a second set of sensor measurements that corresponds to the scene represented in the annotations of the first set.
* The system identifies annotations within this spatial region that indicate the location of the characteristic object in the three-dimensional space.

== Potential Applications ==
This technology could be applied in various fields such as augmented reality, object tracking, and surveillance systems.

== Problems Solved ==
This technology solves the problem of accurately identifying and tracking the location of objects in a three-dimensional space using sensor measurements.

== Benefits ==
The benefits of this technology include improved object localization, enhanced scene understanding, and increased accuracy in object tracking.

== Potential Commercial Applications ==
One potential commercial application of this technology could be in the development of advanced surveillance systems for security purposes.

== Possible Prior Art ==
One possible prior art could be existing object tracking systems that use sensor measurements for localization and tracking.

== Unanswered Questions ==

=== How does the system handle occlusions or obstructions in the scene? ===
The system may face challenges in accurately identifying the location of objects when there are occlusions or obstructions in the scene. Further research may be needed to address this issue.

=== What is the computational complexity of the annotation system? ===
It is important to understand the computational resources required to implement and operate the annotation system effectively. Further analysis may be needed to determine the system's efficiency and scalability.


==Original Abstract Submitted==

an annotation system uses annotations for a first set of sensor measurements from a first sensor to identify annotations for a second set of sensor measurements from a second sensor. the annotation system identifies reference annotations in the first set of sensor measurements that indicates a location of a characteristic object in the two-dimensional space. the annotation system determines a spatial region in the three-dimensional space of the second set of sensor measurements that corresponds to a portion of the scene represented in the annotation of the first set of sensor measurements. the annotation system determines annotations within the spatial region of the second set of sensor measurements that indicates a location of the characteristic object in the three-dimensional space.



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