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US 2025/0209651 A1Published application
Methods, systems and computer programs for relative depth map image generation
AssigneeMaxar International Sweden AB
InventorsTim Yngesjö, Sanna Ringqvist, Simon Wold, Simon Sandin
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Abstract
The present disclosure relates to a method for generating a relative depth map image. The method comprises feeding at least two input images to a neural network, the input images relating to a region of interest at different time periods, the input images being obtained at corresponding arbitrary positions and attitudes with respect to the region of interest, and predicting, using the neural network, the relative depth map image.
Claims13
A method for training a neural network to generate a relative depth map image, the method comprising:
- obtaining a first set of images relating to a region of interest within a first time period;
- obtaining a second set of images relating to the region of interest within a second time period;
- generating a first depth map image based on the first set of images, the first depth map image relating to a depth of the region of interest when observed at a certain attitude and position with respect to the region of interest;
- generating a second depth map image based on the second set of images, the second depth map image relating to a depth of the region of interest when observed at the corresponding attitude and position with respect to the region of interest as the first depth map image;
- generating a first relative depth map image based on a difference between the first depth map image and the second depth map image;
- generating, using the neural network, a second relative depth map image, based on a first input image comprising at least one of:
- the first depth map image, an image of the first set of images, an image generated from a 3D-model of the region of interest at the first time period, and a second input image comprising at least one of:
- an image of the second set of images, an image generated from a 3D-model of the region of interest at the second time period, wherein the first input image and the second input image have the corresponding attitude and position with respect to the region of interest;
- and
- changing parameters of the neural network based on a difference between the second relative depth map image and the first relative depth map image.
7 more elements
A method for generating a relative depth map image, the method comprising:
- obtaining a first input image relating to a region of interest observed at a first time period and at a specific attitude and position relative to the region of interest, the first input image comprising at least one of:
- a first depth map image of the region of interest when observed at said attitude, position and first time period, an image of the region of interest when observed at said attitude, position and first time period, an image generated from a 3D-model of the region of interest at the first time period, the image generated from the 3D-model being generated at said attitude and position with respect to the region of interest;
- obtaining a second input image relating to the region of interest observed at a second time period and at the corresponding attitude and position relative to the region of interest as for the first input image, the second input image comprising at least one of:
- an image of the region of interest when observed at said attitude, position and second time period, an image generated from a 3D-model of the region of interest at the second time period, the image generated from the 3D-model being generated at said attitude and position with respect to the region of interest;
- and
- generating, using a neural network, the relative depth map image, based on the obtained first and second input images.
3 more elements
A system for generating a relative depth map image, the system comprising processing circuitry configured to:
- obtain a first input image relating to a region of interest observed at a first time period and at a specific attitude and position relative to the region of interest, the first input image comprising at least one of:
- a first depth map image of the region of interest when observed at said attitude, position and first time period, an image of the region of interest when observed at said attitude, position and first time period, an image generated from a 3D-model of the region of interest at the first time period, the image generated from the 3D-model being generated at said attitude and position with respect to the region of interest;
- obtain a second input image relating to the region of interest observed at a second time period and at the corresponding attitude and position relative to the region of interest as for the first input image, the second input image comprising at least one of:
- an image of the region of interest when observed at said attitude, position and second time period, an image generated from a 3D-model of the region of interest at the second time period, the image generated from the 3D-model being generated at said attitude and position with respect to the region of interest;
- and
- generate, using a neural network, the relative depth map image, based on the obtained first and second input images.
3 more elements
Dependencies are inferred from the claim text.