Learning Image Processing Tasks from Scene Reconstructions
First Claim
1. A method of image processing comprising:
- receiving a plurality of first input empirical images of a scene;
at a processor, calculating a 2D or higher dimensional reconstruction of the scene from the first input images;
forming training data from the reconstruction of the scene and the first input images,using the training data to learn at least one parameter of a function for transforming an image;
receiving a second input image;
transforming the second input image using the function and the at least one parameter.
2 Assignments
0 Petitions
Accused Products
Abstract
Learning image processing tasks from scene reconstructions is described where the tasks may include but are not limited to: image de-noising, image in-painting, optical flow detection, interest point detection. In various embodiments training data is generated from a 2 or higher dimensional reconstruction of a scene and from empirical images of the same scene. In an example a machine learning system learns at least one parameter of a function for performing the image processing task by using the training data. In an example, the machine learning system comprises a random decision forest. In an example, the scene reconstruction is obtained by moving an image capture apparatus in an environment where the image capture apparatus has an associated dense reconstruction and camera tracking system.
-
Citations
20 Claims
-
1. A method of image processing comprising:
-
receiving a plurality of first input empirical images of a scene; at a processor, calculating a 2D or higher dimensional reconstruction of the scene from the first input images; forming training data from the reconstruction of the scene and the first input images, using the training data to learn at least one parameter of a function for transforming an image; receiving a second input image; transforming the second input image using the function and the at least one parameter. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
-
-
9. A method of image processing comprising:
-
receiving at least one input image; at a processor, transforming the input image using a function having at least one parameter which has been learnt from training data which has been obtained from a 2D, or higher dimensional, reconstruction of a scene reconstructed from empirical data. - View Dependent Claims (10, 11, 12)
-
-
13. An image processing system comprising:
-
an input arranged to receive a sequence of first input empirical images of a scene obtained from a camera moving in the scene; a processor arranged to calculate a 2D or higher dimensional reconstruction of the scene from the first input images and also to track a location and orientation of the camera; the processor being arranged to form training data from the reconstruction of the scene, the tracked camera location and orientation, and at least some of the first input images, a machine learning system arranged to use the training data to learn at least one parameter of a function for transforming an image; the input being arranged to receive a second input image; the machine learning system being arranged to transform the second input image using the function and the at least one parameter. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20)
-
Specification