18159670. SYSTEMS AND METHODS FOR TARGET ASSIGNMENT FOR END-TO-END THREE-DIMENSIONAL (3D) DETECTION simplified abstract (TOYOTA RESEARCH INSTITUTE, INC.)
Contents
- 1 SYSTEMS AND METHODS FOR TARGET ASSIGNMENT FOR END-TO-END THREE-DIMENSIONAL (3D) DETECTION
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 SYSTEMS AND METHODS FOR TARGET ASSIGNMENT FOR END-TO-END THREE-DIMENSIONAL (3D) DETECTION - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Key Features and Innovation
- 1.6 Potential Applications
- 1.7 Problems Solved
- 1.8 Benefits
- 1.9 Commercial Applications
- 1.10 Questions about 3D Object Detection Technology
- 1.11 Original Abstract Submitted
SYSTEMS AND METHODS FOR TARGET ASSIGNMENT FOR END-TO-END THREE-DIMENSIONAL (3D) DETECTION
Organization Name
TOYOTA RESEARCH INSTITUTE, INC.
Inventor(s)
DENNIS Park of Fremont CA (US)
DIAN Chen of Los Altos CA (US)
VITOR Guizilini of Santa Clara CA (US)
ADRIEN D. Gaidon of Los Altos CA (US)
SYSTEMS AND METHODS FOR TARGET ASSIGNMENT FOR END-TO-END THREE-DIMENSIONAL (3D) DETECTION - A simplified explanation of the abstract
This abstract first appeared for US patent application 18159670 titled 'SYSTEMS AND METHODS FOR TARGET ASSIGNMENT FOR END-TO-END THREE-DIMENSIONAL (3D) DETECTION
Simplified Explanation
The patent application describes systems and methods for improved 3D object detection from images, particularly for autonomous vehicles. By predicting 3D bounding boxes and dense depth, the technology enhances object detection accuracy in a vehicle's surrounding environment.
- Utilizes a processor device to predict 3D bounding boxes and dense depth for object detection.
- Enhances object detection accuracy in a vehicle's surrounding environment.
- Enables autonomous operations based on the detected objects.
- Achieves significant improvements in object detection compared to previous methods.
- Simplifies the end-to-end functionality for enhanced performance.
Key Features and Innovation
- Predicts 3D bounding boxes and dense depth for object detection.
- Enhances accuracy in detecting objects in a vehicle's surrounding environment.
- Enables autonomous operations based on the detected objects.
- Achieves significant improvements in object detection accuracy.
- Simplifies the end-to-end functionality for optimized performance.
Potential Applications
The technology can be applied in various industries such as autonomous vehicles, robotics, surveillance systems, and augmented reality for enhanced object detection capabilities.
Problems Solved
The technology addresses the challenges of accurately detecting objects in a 3D space from images, particularly in the context of autonomous vehicles where precision and efficiency are crucial.
Benefits
- Improved accuracy in 3D object detection.
- Enhanced performance in detecting objects in a vehicle's surrounding environment.
- Simplified end-to-end functionality for optimized operations.
- Increased efficiency in autonomous operations.
Commercial Applications
The technology can be utilized in autonomous vehicles for improved object detection, in robotics for enhanced spatial awareness, in surveillance systems for better monitoring capabilities, and in augmented reality for more realistic virtual object interactions.
Questions about 3D Object Detection Technology
How does the technology predict 3D bounding boxes and dense depth for object detection?
The technology utilizes advanced algorithms and processing techniques to predict the 3D structure of objects in a given space from images.
What are the potential applications of this technology beyond autonomous vehicles?
The technology can also be applied in robotics, surveillance systems, and augmented reality for enhanced object detection capabilities in various industries.
Original Abstract Submitted
Systems and methods for enhanced end-to-end three-dimensional (3-D) object detection are disclosed that improve detecting objects in the 3D space from images, such as monocular camera image that may be captured during the operation the autonomous vehicles. For example, a vehicle can include a processor device detecting one or more objects in a 3D space by predicting 3D bounding boxes and predicting dense depth associated with target assignments. The target assignments correspond to the location of objects within an image of the 3D space of a surrounding environment for the vehicle. The vehicle can also include a controller device that receives the detection of the objects in the 3D space from the processor device and performs autonomous operations. The end-to-end 3D object detection techniques achieve a high level of object detection accuracy, with significant improvements compared to previous methods, due to the simplicity and optimization of its end-to-end functionality.
