Hyundai motor company (20240104935). APPARATUS AND METHOD FOR RECOGNIZING AN OBJECT simplified abstract
Contents
- 1 APPARATUS AND METHOD FOR RECOGNIZING AN OBJECT
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 APPARATUS AND METHOD FOR RECOGNIZING AN OBJECT - 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
APPARATUS AND METHOD FOR RECOGNIZING AN OBJECT
Organization Name
Inventor(s)
Tae Koan Yoo of Seongnam-si (KR)
APPARATUS AND METHOD FOR RECOGNIZING AN OBJECT - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240104935 titled 'APPARATUS AND METHOD FOR RECOGNIZING AN OBJECT
Simplified Explanation
An apparatus for recognizing an object includes a camera that obtains a 2D image, a lidar that obtains a 3D image, and a processor. The processor generates a bird's-eye view (BEV) feature map by extracting features from a two-dimensional plane BEV generated based on 3D information. The processor also generates an image feature map by extracting features of a multi-channel 2D image in which the 3D information is added to the 2D image. The processor also generates a complex feature map by mixing the image feature map and the BEV feature map. The processor also recognizes the object by artificial intelligence learning the complex feature map.
- Camera obtains 2D image
- Lidar obtains 3D image
- Processor generates BEV feature map from 3D information
- Processor generates image feature map by adding 3D information to 2D image
- Processor generates complex feature map by combining image and BEV feature maps
- Object recognition through AI learning complex feature map
Potential Applications
This technology can be applied in autonomous vehicles, robotics, surveillance systems, and augmented reality applications.
Problems Solved
This technology solves the problem of accurately recognizing objects in complex environments by combining 2D and 3D information to generate detailed feature maps.
Benefits
The benefits of this technology include improved object recognition accuracy, enhanced situational awareness, and better decision-making capabilities in various applications.
Potential Commercial Applications
The potential commercial applications of this technology include autonomous driving systems, security and surveillance systems, industrial automation, and virtual reality applications.
Possible Prior Art
One possible prior art for this technology could be the use of lidar and camera systems in autonomous vehicles for object recognition and navigation purposes.
Unanswered Questions
How does this technology handle occlusions in object recognition?
The technology uses a combination of 2D and 3D information to generate detailed feature maps, which can help in handling occlusions by providing a more comprehensive understanding of the environment.
What is the computational complexity of the object recognition process?
The computational complexity of the object recognition process depends on the size of the input data, the number of features extracted, and the complexity of the artificial intelligence algorithms used for learning the complex feature map.
Original Abstract Submitted
an apparatus for recognizing an object includes a camera that obtains a 2d image, a lidar that obtains a 3d image, and a processor. the processor generates a bird's-eye view (bev) feature map by extracting features from a two-dimensional plane bev generated based on 3d information. the processor also generates an image feature map by extracting features of a multi-channel 2d image in which the 3d information is added to the 2d image. the processor also generates a complex feature map by mixing the image feature map and the bev feature map. the processor also recognizes the object by artificial intelligence learning the complex feature map.
