De-aliasing depth images
First Claim
1. A machine-implemented method, comprising:
- accessing a depth image that includes a depth value for each of a plurality of locations in the depth image, each of the locations has one or more neighbor locations;
determining a plurality of potential depth values for each of the plurality of locations based on the depth value in the depth image for the location and potential aliasing in the depth image;
determining a cost function based on differences between the potential depth values of each location and its one or more neighbor locations, determining the cost function includes assigning a higher cost for greater differences in potential depth values between a pair of neighbor locations, determining the cost function includes determining whether a pair of neighbor locations are likely to have about the same depth in a scene that corresponds to the depth image, determining the cost function includes penalizing large differences in potential depth values between pairs of neighbor locations that are determined to likely have about the same depth, the determining whether a pair of neighbor locations are likely to have about the same depth in a scene that corresponds to the depth image includes;
accessing a brightness image of the scene that corresponds to the depth image;
detecting edges in the brightness image; and
determining whether the pair of neighbor locations are likely to be at about the same depth based on the detected edges, the penalizing large difference in potential depth values between the pair of neighbor locations that are determined to likely have about the same depth includes increasing the cost of the pair of neighbor locations that are not near a strong edge, further comprising ignoring large differences in depth for pixels that are near a strong edge; and
substantially minimizing the cost function to select one of the potential depth values for each of the locations.
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Accused Products
Abstract
Techniques are provided for de-aliasing depth images. The depth image may have been generated based on phase differences between a transmitted and received modulated light beam. A method may include accessing a depth image that has a depth value for a plurality of locations in the depth image. Each location has one or more neighbor locations. Potential depth values are determined for each of the plurality of locations based on the depth value in the depth image for the location and potential aliasing in the depth image. A cost function is determined based on differences between the potential depth values of each location and its neighboring locations. Determining the cost function includes assigning a higher cost for greater differences in potential depth values between neighboring locations. The cost function is substantially minimized to select one of the potential depth values for each of the locations.
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Citations
15 Claims
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1. A machine-implemented method, comprising:
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accessing a depth image that includes a depth value for each of a plurality of locations in the depth image, each of the locations has one or more neighbor locations; determining a plurality of potential depth values for each of the plurality of locations based on the depth value in the depth image for the location and potential aliasing in the depth image; determining a cost function based on differences between the potential depth values of each location and its one or more neighbor locations, determining the cost function includes assigning a higher cost for greater differences in potential depth values between a pair of neighbor locations, determining the cost function includes determining whether a pair of neighbor locations are likely to have about the same depth in a scene that corresponds to the depth image, determining the cost function includes penalizing large differences in potential depth values between pairs of neighbor locations that are determined to likely have about the same depth, the determining whether a pair of neighbor locations are likely to have about the same depth in a scene that corresponds to the depth image includes; accessing a brightness image of the scene that corresponds to the depth image; detecting edges in the brightness image; and determining whether the pair of neighbor locations are likely to be at about the same depth based on the detected edges, the penalizing large difference in potential depth values between the pair of neighbor locations that are determined to likely have about the same depth includes increasing the cost of the pair of neighbor locations that are not near a strong edge, further comprising ignoring large differences in depth for pixels that are near a strong edge; and substantially minimizing the cost function to select one of the potential depth values for each of the locations. - View Dependent Claims (2, 3, 4, 5, 6)
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7. An apparatus, comprising:
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a processor; and a computer readable storage medium coupled to the processor, the computer readable storage medium having instructions stored thereon which, when executed on the processor cause the processor to access a depth image that includes a depth value for a plurality of locations, each of the locations has one or more neighbor locations, the instructions further cause the processor to access a depth window associated with the depth image, the instructions further cause the processor to determine a plurality of potential depth values for each of the plurality of locations based on the depth value in the depth image and potential aliasing in the depth image, the potential aliasing is based on the depth window, the instructions further cause the processor to determine a cost function based on differences between the potential depth values of each location and its one or more neighbor locations, to determine the cost function the processor assigns a higher cost for greater differences in potential depth values between a pair of neighbor locations, the instructions further cause the processor to substantially minimize the cost function to select one of the potential depth values for each of the locations, wherein the instruction which cause the processor to determine the cost function further cause the processor to determine whether a pair of neighbor locations are likely to have about the same depth in a scene that corresponds to depth image and to penalize large differences in potential depth values between the pair of neighbor locations that are determined to likely to have about the same depth, wherein the instructions further cause the processor to access a brightness image of the scene that corresponds to the depth image, detect edges in the brightness image, and deterring whether the pair of neighbor locations are likely to be at about the same depth based on the detected edges, the instructions further cause the processor to increase the cost of the pair of neighbor locations that are not near a strong edge and to ignore large difference in depth values for pixels that are near a strong edge. - View Dependent Claims (8, 9, 10, 11, 12)
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13. A machine-implemented method, comprising:
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generating a depth image that includes a plurality of pixels, each pixel has one or more neighbor pixels, each pixel having a depth value, the depth image having a depth window; determining a plurality of potential depth values for each of the plurality of pixels based on the depth window and the depth value in the depth image for the pixel; generating a graph that includes a plurality of layers of nodes, each pixel is represented by one node in each layer, the potential depth values for a given pixel are represented by nodes in different layers, pairs of nodes that correspond to neighbor pixels are connected by edges; assigning a cost to each of the edges, the cost of a given edge is based on a depth difference between the potential depth values of the pair of nodes that are connected by the edge; accessing a brightness image of a scene that corresponds to the depth image; detecting edges in the brightness image; determining pairs of neighbor pixels that are likely to be at the same depth in the scene based on the detected edges; for pairs of neighbor pixels that are likely to be at the same depth in the scene, determining which edges connect nodes that have a difference in potential depth values that is greater than a pre-determined threshold; the assigning a cost to each of the edges includes increasing the cost of the edges that connect nodes that have a difference in potential depth values that is greater than a pre-determined threshold; and for pairs of neighbor pixels that are not likely to be at the same depth in the scene, for assigning a cost to each of the edges included decreasing the cost of the edges that connect nodes that have a difference in potential depth values that is greater than a pre-determined threshold; and reducing the graph to a single layer based on minimizing the costs of remaining edges, each of the pixels has one node in the reduced graph. - View Dependent Claims (14, 15)
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Specification