NVIDIA Corporation (20240249538). LONG-RANGE 3D OBJECT DETECTION USING 2D BOUNDING BOXES simplified abstract
Contents
LONG-RANGE 3D OBJECT DETECTION USING 2D BOUNDING BOXES
Organization Name
Inventor(s)
Zetong Yang of Rockville MD (US)
Zhiding Yu of Cupertino CA (US)
Chris Choy of Los Angeles CA (US)
Anima Anandkumar of Pasadena CA (US)
Jose M. Alvarez Lopez of Mountain View CA (US)
LONG-RANGE 3D OBJECT DETECTION USING 2D BOUNDING BOXES - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240249538 titled 'LONG-RANGE 3D OBJECT DETECTION USING 2D BOUNDING BOXES
Abstract: 3D object detection is a computer vision task that involves detecting objects in 3D space from 2D images or videos. Current techniques rely on machine learning processes trained on annotated images with high-quality 3D information, often obtained using lidar technology. However, existing solutions do not support detection beyond the lidar range, limiting applications like autonomous driving.
- Simplified Explanation:
The patent application introduces a technique for 3D object detection that enables long-range detection beyond the limitations of lidar technology.
- Key Features and Innovation:
- Supports long-range detection of 3D objects - Overcomes the limitations of current machine learning solutions - Addresses the need for safety-critical applications like autonomous driving
- Potential Applications:
- Autonomous driving systems - Surveillance and security systems - Robotics and automation - Augmented reality applications - Industrial inspection and monitoring
- Problems Solved:
- Limited measurable range of lidar technology - Inability to detect 3D objects beyond lidar range - Safety-critical requirements for autonomous driving applications
- Benefits:
- Enhanced safety in autonomous driving - Improved accuracy in 3D object detection - Expanded range of applications for computer vision technology
- Commercial Applications:
Title: Long-Range 3D Object Detection Technology for Autonomous Driving and Beyond This technology can be utilized in the development of advanced autonomous driving systems, enhancing safety and reliability. It also has potential applications in surveillance, robotics, augmented reality, and industrial automation, opening up new commercial opportunities in various industries.
- Questions about 3D Object Detection Technology:
1. How does this technology improve upon existing 3D object detection methods? This technology enables long-range detection beyond the limitations of lidar technology, addressing safety-critical requirements for applications like autonomous driving.
2. What are the potential implications of this technology for the future of computer vision and artificial intelligence? This technology could lead to advancements in various fields, including autonomous systems, robotics, and augmented reality, by enabling more accurate and reliable 3D object detection beyond current limitations.
Original Abstract Submitted
3d object detection is a computer vision task that generally detects (e.g. classifies and localizes) objects in 3d space from the 2d images or videos that capture the objects. current techniques used for 3d object detection rely on machine learning processes that learn to detect 3d objects from existing images annotated with high-quality 3d information including depth information generally obtained using lidar technology. however, due to lidar's limited measurable range, current machine learning solutions to 3d object detection do not support detection of 3d objects beyond the lidar range, which is needed for numerous applications, including autonomous driving applications where existing close or midrange 3d object detection does not always meet the safety-critical requirement of autonomous driving. the present disclosure provides for 3d object detection using a technique that supports long-range detection (i.e. detection beyond the lidar range).
