Qualcomm incorporated (20240221395). 3D LANE AND ROAD BOUNDARY ESTIMATION VIA ROW-WISE CLASSIFICATION simplified abstract
Contents
3D LANE AND ROAD BOUNDARY ESTIMATION VIA ROW-WISE CLASSIFICATION
Organization Name
Inventor(s)
Behnaz Rezaei of San Diego CA (US)
Christopher Brunner of San Diego CA (US)
3D LANE AND ROAD BOUNDARY ESTIMATION VIA ROW-WISE CLASSIFICATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240221395 titled '3D LANE AND ROAD BOUNDARY ESTIMATION VIA ROW-WISE CLASSIFICATION
Simplified Explanation: This patent application describes systems, methods, and devices for vehicle driving assistance systems that utilize image processing techniques. The method involves receiving image data from a sensor, extracting point features from LiDAR data, partitioning the point features, performing feature pooling, and determining lane-boundary heads based on the pooled features.
- Image processing method for vehicle driving assistance systems
- Utilizes LiDAR data and point features
- Involves feature pooling and determining lane-boundary heads
- Includes row-wise classification and regression processing
- Supports offset correction and height regression processing
Potential Applications: 1. Autonomous driving systems 2. Advanced driver assistance systems (ADAS) 3. Traffic management systems
Problems Solved: 1. Enhancing lane detection accuracy 2. Improving road safety 3. Optimizing vehicle navigation
Benefits: 1. Increased precision in lane boundary detection 2. Enhanced overall driving assistance capabilities 3. Improved efficiency in image processing algorithms
Commercial Applications: Title: Advanced Image Processing for Vehicle Driving Assistance Systems This technology can be utilized by automotive manufacturers, technology companies, and transportation authorities to develop cutting-edge driving assistance systems for various vehicles. The market implications include improved safety features, enhanced navigation systems, and potential partnerships with autonomous vehicle companies.
Prior Art: Readers can explore prior patents related to LiDAR data processing, image recognition in vehicles, and lane detection algorithms to gain a deeper understanding of the existing technology landscape in this field.
Frequently Updated Research: Researchers in the field of computer vision and autonomous driving are continuously exploring new algorithms and techniques to enhance image processing capabilities for driving assistance systems. Stay updated on the latest advancements in LiDAR technology and feature extraction methods for improved lane detection.
Questions about Image Processing for Vehicle Driving Assistance Systems: 1. How does LiDAR data contribute to the accuracy of lane detection in driving assistance systems? 2. What are the key differences between row-wise classification and vertex-wise regression processing in image processing algorithms for vehicles?
Original Abstract Submitted
this disclosure provides systems, methods, and devices for vehicle driving assistance systems that support image processing. in a first aspect, a method of image processing includes receiving image data from an image sensor; extracting point features from light detection and ranging (lidar) data; partitioning the point features; performing bev-feature pooling based on the partitioned point features; determining lane-boundary heads based on the bev-feature pooling, wherein the determining comprises row-wise classification with at least one of: offset correction regression processing; or vertex-wise height regression processing. other aspects and features are also claimed and described.
