POINT CLOUD NOISE AND OUTLIER REMOVAL FOR IMAGE-BASED 3D RECONSTRUCTION
First Claim
1. A method for reconstructing a three-dimensional (3D) model of an object, the method being performed by a computer system and comprising:
- receiving images of the object, the images capturing the object from different viewpoints;
obtaining a depth map for each of the images, the depth map including information relating to a surface of the object in the 3D space;
projecting each pixel in each depth map into a 3D space to obtain a point set;
for each point in the point set, determining whether the point is consistent with the surface of the object in the 3D space as indicated by a set of depth maps for the images, wherein the set of depth maps does not include the depth map from which the point is projected, wherein the consistency determination includes;
for each depth map in the set;
performing an intersection of a ray with the surface of the object indicated by the depth map to find an intersection point, the ray being through a camera viewpoint corresponding to the depth map, and the point; and
in response to the intersection point being found, determining a distance between the point and intersection point as a distance between the point and the surface of the object as seen from the camera viewpoint corresponding to the depth map;
determining whether the point is geometrically consistent with the surface of the object based on one or more of the determined distances between the point and the surface of the object; and
determining whether to discard the point from point set based on the determination whether the point is geometrically consistent with the surface of the object; and
reconstructing the 3D model using the point set.
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Accused Products
Abstract
Enhanced removing of noise and outliers from one or more point sets generated by image-based 3D reconstruction techniques is provided. In accordance with the disclosure, input images and corresponding depth maps can be used to remove pixels that are geometrically and/or photometrically inconsistent with the colored surface implied by the input images. This allows standard surface reconstruction methods (such as Poisson surface reconstruction) to perform less smoothing and thus achieve higher quality surfaces with more features. In some implementations, the enhanced point-cloud noise removal in accordance with the disclosure can include computing per-view depth maps, and detecting and removing noisy points and outliers from each per-view point cloud by checking if points are consistent with the surface implied by the other input views.
27 Citations
20 Claims
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1. A method for reconstructing a three-dimensional (3D) model of an object, the method being performed by a computer system and comprising:
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receiving images of the object, the images capturing the object from different viewpoints; obtaining a depth map for each of the images, the depth map including information relating to a surface of the object in the 3D space; projecting each pixel in each depth map into a 3D space to obtain a point set; for each point in the point set, determining whether the point is consistent with the surface of the object in the 3D space as indicated by a set of depth maps for the images, wherein the set of depth maps does not include the depth map from which the point is projected, wherein the consistency determination includes; for each depth map in the set; performing an intersection of a ray with the surface of the object indicated by the depth map to find an intersection point, the ray being through a camera viewpoint corresponding to the depth map, and the point; and in response to the intersection point being found, determining a distance between the point and intersection point as a distance between the point and the surface of the object as seen from the camera viewpoint corresponding to the depth map; determining whether the point is geometrically consistent with the surface of the object based on one or more of the determined distances between the point and the surface of the object; and determining whether to discard the point from point set based on the determination whether the point is geometrically consistent with the surface of the object; and reconstructing the 3D model using the point set. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 12)
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11. A system for reconstructing a three-dimensional (3D) model of an object, the system comprising one or more of a processor configured to execute machine-readable instructions such that when the machine-readable instructions are executed by the processor, the processor is caused to perform:
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receiving images of the object, the images capturing the object from different viewpoints; obtaining a depth map for each of the images, the depth map including information relating to a surface of the object in the 3D space; projecting each pixel point in each depth map into a 3D space to obtain a point set; for each point in the point set, determining whether the point is consistent with the surface of the object in the 3D space as indicated by a set of depth maps for the images, wherein the set of depth maps does not include the depth map from which the point is projected, wherein the consistency determination includes; for each depth map in the set; performing an intersection of a ray with the surface of the object indicated by the depth map to find an intersection point, the ray being through a camera viewpoint corresponding to the depth map, and the point; and in response to the intersection point being found, determining a distance between the point and intersection point as a distance between the point and the surface of the object as seen from the camera viewpoint corresponding to the depth map; determining whether the point is geometrically consistent with the surface of the object based on one or more of the determined distances between the point and the surface of the object; and determining whether to discard the point from point set based on the determination whether the point is geometrically consistent with the surface of the object; and reconstructing the 3D model using the point set. - View Dependent Claims (13, 14, 15, 16, 17, 18, 19, 20)
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Specification