Samsung electronics co., ltd. (20240161322). METHOD AND APPARATUS WITH DEPTH INFORMATION ESTIMATION simplified abstract
Contents
- 1 METHOD AND APPARATUS WITH DEPTH INFORMATION ESTIMATION
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 METHOD AND APPARATUS WITH DEPTH INFORMATION ESTIMATION - 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
METHOD AND APPARATUS WITH DEPTH INFORMATION ESTIMATION
Organization Name
Inventor(s)
METHOD AND APPARATUS WITH DEPTH INFORMATION ESTIMATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240161322 titled 'METHOD AND APPARATUS WITH DEPTH INFORMATION ESTIMATION
Simplified Explanation
The method described in the abstract involves using a simulator to generate simulated images based on depth maps, training an artificial neural network model using these simulated images and depth maps, and then using this trained model to estimate depth information from actual images.
- Simulator used to generate simulated images based on depth maps
- Artificial neural network model trained using simulated images and depth maps
- Actual images inputted into trained model to generate depth maps
- Second simulated images generated using the second depth map
Potential Applications
This technology could be applied in various fields such as:
- Augmented reality
- Autonomous driving
- Robotics
- Medical imaging
Problems Solved
This technology helps in:
- Accurately estimating depth information from images
- Improving the performance of depth estimation algorithms
- Enhancing the quality of simulated images
Benefits
The benefits of this technology include:
- Increased accuracy in depth estimation
- Improved performance of artificial neural network models
- Enhanced quality of simulated images
Potential Commercial Applications
This technology could be commercially applied in:
- Virtual reality systems
- Surveillance systems
- 3D modeling software
- Image editing tools
Possible Prior Art
One possible prior art for this technology could be the use of artificial neural networks for image processing and depth estimation. Additionally, simulators have been used in various industries for generating realistic simulations.
Unanswered Questions
How does this technology compare to existing depth estimation methods?
This article does not provide a direct comparison to existing depth estimation methods.
What are the limitations of this technology in real-world applications?
This article does not address the potential limitations of implementing this technology in real-world scenarios.
Original Abstract Submitted
a method of estimating depth information includes generating a first simulated image using a simulator provided with a first depth map, training an artificial neural network model based on the first depth map and the first simulated image, generating a second depth map by inputting an actual image into the trained artificial neural network model, and generating a second simulated image using the simulator provided with the second depth map.
