Qualcomm incorporated (20240096111). DETERMINING LANE ASSOCIATIONS BASED ON IMAGES simplified abstract
Contents
- 1 DETERMINING LANE ASSOCIATIONS BASED ON IMAGES
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 DETERMINING LANE ASSOCIATIONS BASED ON IMAGES - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
DETERMINING LANE ASSOCIATIONS BASED ON IMAGES
Organization Name
Inventor(s)
Shivam Agarwal of Sunnyvale CA (US)
Avdhut Joshi of San Marcos CA (US)
Jayakrishnan Unnikrishnan of Bellevue WA (US)
Yoga Y Nadaraajan of Poway CA (US)
Sree Sesha Aravind Vadrevu of San Diego CA (US)
Gautam Sachdeva of San Diego CA (US)
DETERMINING LANE ASSOCIATIONS BASED ON IMAGES - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240096111 titled 'DETERMINING LANE ASSOCIATIONS BASED ON IMAGES
Simplified Explanation
The patent application describes systems and techniques for determining lane associations of target vehicles.
- Obtaining a two-dimensional bounding box defining a position within an image frame associated with a target vehicle
- Obtaining lane markers defining a position within the image frame associated with at least one lane boundary
- Associating a lane with the target vehicle based on the relationship between the two-dimensional bounding box and the lane markers
Potential Applications
This technology could be applied in autonomous vehicles, advanced driver-assistance systems (ADAS), traffic management systems, and surveillance systems.
Problems Solved
This technology helps in accurately determining the lane associations of target vehicles, which is crucial for various applications such as autonomous driving and traffic monitoring.
Benefits
The benefits of this technology include improved accuracy in lane association determination, enhanced safety on the roads, and better traffic flow management.
Potential Commercial Applications
Potential commercial applications of this technology include automotive industry for autonomous vehicles, traffic control authorities for traffic monitoring, and surveillance companies for security systems.
Possible Prior Art
One possible prior art could be the use of computer vision techniques for lane detection and vehicle tracking in the field of autonomous driving and ADAS.
Unanswered Questions
How does this technology handle occlusions in the image frame?
This technology may use advanced algorithms to predict the position of the target vehicle and its lane association even in the presence of occlusions.
What is the computational cost of implementing this technology in real-time systems?
The computational cost of this technology may vary depending on the complexity of the algorithms used, but efforts are made to optimize it for real-time applications.
Original Abstract Submitted
systems and techniques are described herein for determining lane associations of target vehicles. for instance, a method for determining lane associations of target vehicles is provided. the method may include obtaining a two-dimensional bounding box defining a position within an image frame that is associated with a target vehicle; obtaining lane markers defining a position within the image frame that is associated with at least one lane boundary; and associating a lane with the target vehicle based on a relationship between the two-dimensional bounding box and the lane markers.
