COMPUTER VISION SYSTEM AND METHOD
First Claim
Patent Images
1. An image processing method for segmenting an image, the method comprising:
- receiving first image;
producing a second image from said first image, wherein said second image is a lower resolution representation of said first image;
processing said first image with a first processing stage to produce a first feature map;
processing said second image with a second processing stage to produce a second feature map; and
combining the first feature map with the second feature map to produce a semantic segmented image;
wherein the first processing stage comprises a first neural network comprising at least one separable convolution module configured to perform separable convolution and said second processing stage comprises a second neural network comprising at least one separable convolution module configured to perform separable convolution;
the number of layers in the first neural network being smaller than the number of layers in the second neural network.
1 Assignment
0 Petitions
Accused Products
Abstract
An image processing method for segmenting an image, the method comprising:
- receiving first image;
- producing a second image from said first image, wherein said second image is a lower resolution representation of said first image;
- processing said first image with a first processing stage to produce a first feature map;
- processing said second image with a second processing stage to produce a second feature map; and
- combining the first feature map with the second feature map to produce a semantic segmented image;
- wherein the first processing stage comprises a first neural network comprising at least one separable convolution module configured to perform separable convolution and said second processing stage comprises a second neural network comprising at least one separable convolution module configured to perform separable convolution; the number of layers in the first neural network being smaller than the number of layers in the second neural network.
-
Citations
20 Claims
-
1. An image processing method for segmenting an image, the method comprising:
-
receiving first image; producing a second image from said first image, wherein said second image is a lower resolution representation of said first image; processing said first image with a first processing stage to produce a first feature map; processing said second image with a second processing stage to produce a second feature map; and combining the first feature map with the second feature map to produce a semantic segmented image; wherein the first processing stage comprises a first neural network comprising at least one separable convolution module configured to perform separable convolution and said second processing stage comprises a second neural network comprising at least one separable convolution module configured to perform separable convolution;
the number of layers in the first neural network being smaller than the number of layers in the second neural network. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 20)
-
-
15. A method of training a model, said model for segmenting an image, the model comprising:
-
a first neural network having a plurality of layers comprising at least one separable convolution module configured to perform separable convolutions; a second neural network with a plurality of layers, comprising at least one separable convolution module configured to perform separable convolutions;
the number of layers in the first neural network being smaller than the number of layers in the second neural network,the first neural network being configured to process an image at a first resolution and the second neural network being configured to process the same image at a lower resolution, the feature map of the first and second neural networks being combined by addition at a single stage; the training method comprising; providing training data, the training data comprising images and semantic segmented information concerning said images; training said model using said images as the input and the semantic segmented info as the output, wherein the two stages are trained together. - View Dependent Claims (16, 17)
-
-
18. An image processing system for segmenting an image, the system comprising:
-
an interface and a processor, said interface having an image input and being adapted to receive a first image, said processor being adapted to; produce a second image from said first image, wherein said second image is a lower resolution representation of said first image; process said first image with a first processing stage to produce a first feature map; process said second image with a second processing stage to produce a second feature map; and combine the first feature map with the second feature map to produce a semantic segmented image; wherein the first processing stage comprises a first neural network comprising at least one separable convolution module configured to perform separable convolution and said second processing stage comprises a second neural network comprising at least one separable convolution module configured to perform separable convolution;
the number of layers in the first neural network being smaller than the number of layers in the second neural network. - View Dependent Claims (19)
-
Specification