18411138. Camera Parameter Estimation Using Semantic Labels simplified abstract (Apple Inc.)
Contents
- 1 Camera Parameter Estimation Using Semantic Labels
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 Camera Parameter Estimation Using Semantic Labels - 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
Camera Parameter Estimation Using Semantic Labels
Organization Name
Inventor(s)
Payal Jotwani of Santa Clara CA (US)
Camera Parameter Estimation Using Semantic Labels - A simplified explanation of the abstract
This abstract first appeared for US patent application 18411138 titled 'Camera Parameter Estimation Using Semantic Labels
Simplified Explanation
The patent application describes a device that can estimate the intrinsic parameter of a camera based on two-dimensional and three-dimensional coordinates obtained from a point cloud and a corresponding two-dimensional image of a scene.
- Device obtains a point cloud of a scene with three-dimensional coordinates.
- First cluster of points in the point cloud has a first semantic label.
- Device captures a two-dimensional image of the scene with a camera.
- Device detects a representation of a first object in the two-dimensional image.
- Device determines two-dimensional coordinates of the first object in the image.
- Device maps the two-dimensional coordinates to three-dimensional coordinates in the point cloud.
- Device estimates the intrinsic parameter of the camera based on the coordinates.
Potential Applications
This technology could be applied in:
- Augmented reality systems
- Autonomous navigation systems
- Robotics for object recognition and localization
Problems Solved
This technology solves the following problems:
- Estimating camera parameters accurately
- Mapping two-dimensional images to three-dimensional space
- Improving object detection and localization accuracy
Benefits
The benefits of this technology include:
- Enhanced accuracy in object detection and localization
- Improved performance of augmented reality applications
- Better calibration of camera systems
Potential Commercial Applications
Potential commercial applications of this technology include:
- Surveillance systems
- Industrial automation
- Virtual reality applications
Possible Prior Art
One possible prior art for this technology could be:
- Camera calibration techniques using point clouds and images
Unanswered Questions
How does this technology handle occlusions in the scene?
The patent application does not specify how the device deals with occlusions in the scene that may affect the accuracy of object detection and localization.
What is the computational complexity of the estimation process?
The patent application does not provide information on the computational resources required for estimating the intrinsic parameter based on the coordinates obtained from the point cloud and the two-dimensional image.
Original Abstract Submitted
A device obtains a point cloud of a scene including a plurality of points. Each point has three-dimensional coordinates in a three-dimensional coordinate system. A first cluster of points has a first semantic label. The device obtains a two-dimensional image of the scene with a camera with an intrinsic parameter. The device detects, in the two-dimensional image, a representation of a first object corresponding to the first semantic label. The device determines two-dimensional coordinates in a two-dimensional coordinate system of the two-dimensional image corresponding to the first object. The device determines, from the first cluster of points, three-dimensional coordinates in the three-dimensional coordinate system of the scene corresponding to the two-dimensional coordinates in the two-dimensional coordinate system of the two-dimensional image of the scene. The device estimates the intrinsic parameter based on the two-dimensional and the three-dimensional coordinates.
