17933756. DISTANCE ESTIMATION USING A GEOMETRICAL DISTANCE AWARE MACHINE LEARNING MODEL simplified abstract (QUALCOMM Incorporated)
Contents
- 1 DISTANCE ESTIMATION USING A GEOMETRICAL DISTANCE AWARE MACHINE LEARNING MODEL
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 DISTANCE ESTIMATION USING A GEOMETRICAL DISTANCE AWARE MACHINE LEARNING MODEL - 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
DISTANCE ESTIMATION USING A GEOMETRICAL DISTANCE AWARE MACHINE LEARNING MODEL
Organization Name
Inventor(s)
Senthil Kumar Yogamani of Headford (IE)
Varun Ravi Kumar of San Diego CA (US)
DISTANCE ESTIMATION USING A GEOMETRICAL DISTANCE AWARE MACHINE LEARNING MODEL - A simplified explanation of the abstract
This abstract first appeared for US patent application 17933756 titled 'DISTANCE ESTIMATION USING A GEOMETRICAL DISTANCE AWARE MACHINE LEARNING MODEL
Simplified Explanation
The patent application describes techniques and systems for generating depth information for an image by combining features with distance maps to create combined feature distance information.
- Obtaining one or more images of an environment
- Generating a set of features for the images
- Combining the features with distance maps to create combined feature distance information
- Generating depth information based on the combined feature distance information
- Outputting the depth information of the environment
Potential Applications
This technology could be applied in various fields such as:
- Augmented reality
- Autonomous driving
- Robotics
- 3D modeling
Problems Solved
This technology helps in:
- Accurately determining distances in images
- Enhancing depth perception in images
- Improving object recognition in images
Benefits
The benefits of this technology include:
- Enhanced visualization in images
- Improved accuracy in depth information
- Increased efficiency in image processing
Potential Commercial Applications
With its applications in various industries, this technology could be commercially utilized in:
- Surveillance systems
- Medical imaging
- Virtual reality applications
Possible Prior Art
One possible prior art could be the use of stereo vision systems for depth perception in images. Another could be the use of LiDAR technology for generating depth information.
What are the limitations of this technology in real-world applications?
The limitations of this technology in real-world applications include:
- Processing speed may be a concern for real-time applications
- Accuracy of depth information may vary based on environmental conditions
How does this technology compare to existing depth sensing technologies?
This technology offers a unique approach by combining features with distance maps to generate depth information, which may provide more accurate and detailed results compared to traditional depth sensing technologies like LiDAR or stereo vision systems.
Original Abstract Submitted
Techniques and systems are provided for generating depth information for an image. For instance, a process can include obtaining one or more images of an environment. The process can further include generating a set of features for the one or more images. The process can also include combining the set of features with one or more distance maps to generate combined feature distance information, wherein the one or more distance maps indicate distances based on relative height above a ground level. The process can further include generating depth information of the environment based on the combined feature distance information, and outputting the depth information of the environment.
