Qualcomm incorporated (20240095937). DISTANCE ESTIMATION USING A GEOMETRICAL DISTANCE AWARE MACHINE LEARNING MODEL simplified abstract
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 20240095937 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, which is then used to generate depth information of the environment.
- Obtaining one or more images of an environment
- Generating a set of features for the images
- Combining the features with one or more distance maps
- Generating combined feature distance information
- Generating depth information based on the combined information
- Outputting the depth information
Potential Applications
This technology could be applied in various fields such as:
- Augmented reality
- Autonomous driving
- Robotics
- Surveillance systems
Problems Solved
This technology helps in:
- Enhancing image processing capabilities
- Improving depth perception accuracy
- Enabling better understanding of the environment
Benefits
The benefits of this technology include:
- Enhanced visualization
- Improved object recognition
- Accurate distance estimation
Potential Commercial Applications
Potential commercial applications of this technology could include:
- Camera systems for vehicles
- Security cameras
- Virtual reality devices
Possible Prior Art
One possible prior art for this technology could be the use of stereo vision systems for depth perception in images.
Unanswered Questions
How does this technology compare to existing depth sensing technologies?
This article does not provide a direct comparison with existing depth sensing technologies.
What are the limitations of this technology in terms of accuracy and reliability?
The article does not address the limitations of this technology in terms of accuracy and reliability.
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.
