Nvidia corporation (20240312187). FEATURE TRACKING FOR AUTONOMOUS SYSTEMS AND APPLICATIONS simplified abstract
Contents
FEATURE TRACKING FOR AUTONOMOUS SYSTEMS AND APPLICATIONS
Organization Name
Inventor(s)
Yue Wu of Mountain View CA (US)
Cheng-Chieh Yang of Sunnyvale CA (US)
Xin Tong of Santa Clara CA (US)
Minwoo Park of Saratoga CA (US)
FEATURE TRACKING FOR AUTONOMOUS SYSTEMS AND APPLICATIONS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240312187 titled 'FEATURE TRACKING FOR AUTONOMOUS SYSTEMS AND APPLICATIONS
- Simplified Explanation:**
The patent application describes systems and methods for feature tracking in autonomous or semi-autonomous systems by merging features detected by feature trackers and detectors to track features between images.
- Key Features and Innovation:**
- Merging features detected by trackers and detectors for improved feature tracking. - Limiting the number and locations of merged features to focus on important features for tracking. - Prioritizing tracking of features associated with objects near the driving surface in autonomous driving applications.
- Potential Applications:**
- Autonomous driving systems - Robotics - Surveillance systems - Augmented reality applications
- Problems Solved:**
- Enhancing feature tracking accuracy in autonomous systems - Improving object detection and tracking capabilities - Optimizing resource allocation for feature tracking
- Benefits:**
- Increased efficiency in feature tracking - Enhanced object recognition - Improved safety in autonomous systems
- Commercial Applications:**
Title: Advanced Feature Tracking Technology for Autonomous Systems This technology can be utilized in the development of autonomous vehicles, robotics, surveillance systems, and augmented reality applications. It has the potential to revolutionize the way features are tracked and detected in various industries, leading to safer and more efficient operations.
- Questions about Feature Tracking Technology:**
1. How does feature tracking technology improve object detection in autonomous systems? 2. What are the key advantages of merging features detected by trackers and detectors for feature tracking?
Original Abstract Submitted
in various examples, feature tracking for autonomous or semi-autonomous systems and applications is described herein. systems and methods are disclosed that merge, using one or more processes, features detected using a feature tracker(s) and features detected using a feature detector(s) in order to track features between images. in some examples, the number of merged features and/or the locations of the merged features within the images are limited. this way, the systems and methods are able to identify merged features that are of greater importance for tracking while refraining from tracking merged features that are of less importance. for example, if the systems and methods are being used to identify features for autonomous driving, a greater number of merged features that are associated with objects located proximate to the driving surface may be tracked as compared to merged features that are associated with the sky.
