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公开(公告)号：US20240135644A1
公开(公告)日：2024-04-25
申请号：US17971729
申请日：2022-10-23
发明人： Mikko Strandborg , Kimmo Roimela , Pekka Väänänen
摘要： A method including: receiving colour images, depth images, and viewpoint information; dividing 3D space occupied by real-world environment into 3D grid(s) of voxels (204); creating 3D data structure(s) comprising nodes, each node representing corresponding voxel; dividing colour image and depth image into colour tiles and depth tiles, respectively; mapping colour tile to voxel(s) whose colour information is captured in colour tile, based on depth information captured in corresponding depth tile and viewpoint from which colour image and depth image are captured; and storing, in node representing voxel(s), reference information indicative of unique identification of colour tile that captures colour information of voxel(s) and corresponding depth tile that captures depth information, along with viewpoint information indicative of viewpoint from which colour image and depth image are captured.
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公开(公告)号：US20240046556A1
公开(公告)日：2024-02-08
申请号：US17881264
申请日：2022-08-04
发明人： Mikko Strandborg , Kimmo Roimela
CPC分类号： G06T15/503 , G06T19/006 , G06T7/11 , G06T15/205 , G06T3/40 , G06T7/90 , G06T2207/20021 , G06T2207/10028 , G06T2200/08 , G06T2207/10024 , G06T2210/56
摘要： A computer-implemented method including: receiving visible-light images captured from viewpoints using visible-light camera(s); creating 3D model of real-world environment, wherein 3D model stores colour information pertaining to 3D points on surfaces of real objects (204); dividing 3D points into groups of 3D points, based on at least one of: whether surface normal of 3D points in group lie within predefined threshold angle from each other, differences in materials of real objects, differences in textures of surfaces of real objects; for group of 3D points, determining at least two of visible-light images in which group of 3D points is captured from different viewpoints, wherein said images are representative of different surface irradiances of group of 3D points; and storing, in 3D model, information indicative of different surface irradiances.
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公开(公告)号：US20240362862A1
公开(公告)日：2024-10-31
申请号：US18306295
申请日：2023-04-25
发明人： Mikko Strandborg , Kimmo Roimela
CPC分类号： G06T17/005 , G06F3/013 , G06T7/90 , G06V10/25 , G06V10/761 , G06V10/82 , G06T2207/10024 , G06T2207/20081
摘要： A hierarchical data structure has sets of nodes representing a 3D space of an environment at different granularity levels. Sets of neural networks at different granularity levels are trained. For a portion of an output image, a granularity level at which the portion is to be reconstructed is determined. A corresponding node is identified; the node having sets of child nodes. A set of child nodes is selected at the granularity level at which the portion is to be reconstructed. For a child node, a cascade of neural networks is utilised to reconstruct the portion. Granularity level of N+1th neural network is higher than that of Nth neural network. Input of a neural network includes outputs of at least a predefined number of previous neural networks.
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公开(公告)号：US20240282051A1
公开(公告)日：2024-08-22
申请号：US18111340
申请日：2023-02-17
发明人： Kimmo Roimela , Mikko Strandborg
CPC分类号： G06T17/00 , G06T7/11 , G06T7/70 , G06V10/25 , G06V10/761 , G06V10/82 , G06T2207/10024 , G06T2207/10028 , G06T2207/20081
摘要： A system and method for receiving colour images, depth images and viewpoint information; dividing 3D space occupied by real-world environment into 3D grid(s) of voxels; create 3D data structure(s) comprising nodes, each node representing corresponding voxel; dividing colour image and depth image into colour tiles and depth tiles, respectively; mapping colour tile to voxel(s) whose colour information is captured in colour tile; storing, in node representing voxel(s), viewpoint information indicative of viewpoint from which colour and depth images are captured, along with any of: colour tile that captures colour information of voxel(s) and corresponding depth tile that captured depth information, or reference information indicative of unique identification of colour tile and corresponding depth tile; and utilising 3D data structure(s) for training neural network(s), wherein input of neural network(s) comprises 3D position of point and output of neural network(s) comprises colour and opacity of point.
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公开(公告)号：US12045932B2
公开(公告)日：2024-07-23
申请号：US17881264
申请日：2022-08-04
发明人： Mikko Strandborg , Kimmo Roimela
CPC分类号： G06T15/503 , G06T3/40 , G06T7/11 , G06T7/90 , G06T15/205 , G06T19/006 , G06T2200/08 , G06T2207/10024 , G06T2207/10028 , G06T2207/20021 , G06T2210/56
摘要： A computer-implemented method including: receiving visible-light images captured from viewpoints using visible-light camera(s); creating 3D model of real-world environment, wherein 3D model stores colour information pertaining to 3D points on surfaces of real objects (204); dividing 3D points into groups of 3D points, based on at least one of: whether surface normal of 3D points in group lie within predefined threshold angle from each other, differences in materials of real objects, differences in textures of surfaces of real objects; for group of 3D points, determining at least two of visible-light images in which group of 3D points is captured from different viewpoints, wherein said images are representative of different surface irradiances of group of 3D points; and storing, in 3D model, information indicative of different surface irradiances.
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公开(公告)号：US20240233264A9
公开(公告)日：2024-07-11
申请号：US17971729
申请日：2022-10-24
发明人： Mikko Strandborg , Kimmo Roimela , Pekka Väänänen
摘要： A method including: receiving colour images, depth images, and viewpoint information; dividing 3D space occupied by real-world environment into 3D grid(s) of voxels (204); creating 3D data structure(s) comprising nodes, each node representing corresponding voxel; dividing colour image and depth image into colour tiles and depth tiles, respectively; mapping colour tile to voxel(s) whose colour information is captured in colour tile, based on depth information captured in corresponding depth tile and viewpoint from which colour image and depth image are captured; and storing, in node representing voxel(s), reference information indicative of unique identification of colour tile that captures colour information of voxel(s) and corresponding depth tile that captures depth information, along with viewpoint information indicative of viewpoint from which colour image and depth image are captured.
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公开(公告)号：US20240362853A1
公开(公告)日：2024-10-31
申请号：US18306304
申请日：2023-04-25
发明人： Mikko Strandborg , Kimmo Roimela
CPC分类号： G06T15/20 , G06F3/013 , G06T5/77 , G06T7/50 , G06T15/06 , G06T19/006 , G06T19/20 , G06T2207/10024 , G06T2207/10028 , G06T2207/20021 , G06T2207/20081 , G06T2207/20084 , G06T2219/2012
摘要： Disclosed is method including: obtaining neural network(s) trained for rendering images, wherein input of neural network(s) has 3D position of point in real-world environment and output of neural network(s) includes colour and opacity of point; obtaining 3D model(s) of real-world environment; receiving viewpoint from perspective of which image is to be generated; receiving gaze direction; determining region of real-world environment that is to be represented in image, based on viewpoint and field of view of image; determining gaze portion and peripheral portion of region of real-world environment, based on gaze direction, wherein gaze portion corresponds to gaze direction, while peripheral portion surrounds gaze portion; utilising neural network(s) to ray march for gaze portion, to generate gaze segment of image; and utilising 3D model(s) to generate peripheral segment of image.
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公开(公告)号：US20240282050A1
公开(公告)日：2024-08-22
申请号：US18111299
申请日：2023-02-17
发明人： Mikko Strandborg , Kimmo Roimela
CPC分类号： G06T17/00 , G06T7/11 , G06T7/13 , G06T7/90 , G06V10/761 , G06V10/82 , G06T2207/10024 , G06T2207/10028 , G06T2207/20081
摘要： Disclosed is a method and system for: obtaining 3D data structure comprising nodes, each node representing voxel of 3D grid of voxels, wherein node stores viewpoint information, with any of: (i) colour tile that captures colour information of voxel and depth tile, (ii) reference information indicative of unique identification of colour and depth tiles; utilising 3D data structure for training neural network(s), wherein input of neural network(s) comprises 3D position of point in real-world environment and output of neural network(s) comprises colour and opacity of point; and for new viewpoint, determining visible nodes whose voxels are visible from new viewpoint; for visible node, selecting depth tile(s) whose viewpoint(s) matches new viewpoint most closely; reconstructing 2D geometry of objects from depth tiles; and utilising neural network(s) to render colours for pixels of output colour image.
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