Multi-image feature matching using multi-scale oriented patches
First Claim
1. A computer-implemented process for identifying corresponding points among multiple images of a scene, comprising using a computer to perform the following process actions:
- identifying interest points in each image, at varying resolutions, whose locations within the image depicting the point are defined by at least one property attributable to the pixels in a first prescribed-sized neighborhood around the point, and which can be assigned a unique orientation based on least one property attributable to the pixels in a second prescribed-sized neighborhood around the point;
generating a descriptor for each of the interest points which characterizes each point in a manner that is substantially invariant to changes in image location, orientation, and scale, as well as to changes in the intensity of the pixels used to define the location and orientation of the point;
finding substantially matching descriptors among the images; and
designating the interest points associated with each set of matching descriptors that appear in different images as corresponding points.
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Abstract
A system and process for identifying corresponding points among multiple images of a scene is presented. This involves a multi-view matching framework based on a new class of invariant features. Features are located at Harris corners in scale-space and oriented using a blurred local gradient. This defines a similarity invariant frame in which to sample a feature descriptor. The descriptor actually formed is a bias/gain normalized patch of intensity values. Matching is achieved using a fast nearest neighbor procedure that uses indexing on low frequency Haar wavelet coefficients. A simple 6 parameter model for patch matching is employed, and the noise statistics are analyzed for correct and incorrect matches. This leads to a simple match verification procedure based on a per feature outlier distance.
69 Citations
23 Claims
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1. A computer-implemented process for identifying corresponding points among multiple images of a scene, comprising using a computer to perform the following process actions:
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identifying interest points in each image, at varying resolutions, whose locations within the image depicting the point are defined by at least one property attributable to the pixels in a first prescribed-sized neighborhood around the point, and which can be assigned a unique orientation based on least one property attributable to the pixels in a second prescribed-sized neighborhood around the point; generating a descriptor for each of the interest points which characterizes each point in a manner that is substantially invariant to changes in image location, orientation, and scale, as well as to changes in the intensity of the pixels used to define the location and orientation of the point; finding substantially matching descriptors among the images; and designating the interest points associated with each set of matching descriptors that appear in different images as corresponding points. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16)
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17. A system for identifying corresponding points among multiple images of a scene, comprising:
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a general purpose computing device; a computer program comprising program modules executable by the computing device, wherein the computing device is directed by the program modules of the computer program to, identify interest points representing potential corresponding points in each image, wherein each interest point is defined by a location and orientation assigned to it based on the pattern formed by a prescribed property of the pixels in a neighborhood centered around the point; generate a descriptor for each of the interest points which characterizes each point in a manner that is substantially invariant to changes in image location, orientation, and scale, as well as to changes in the bias and gain of the pixels used to define the location and orientation of the point; find substantially matching descriptors among the images; and designate the interest points associated with each set of matching descriptors that appear in different images as corresponding points. - View Dependent Claims (18, 19, 20, 21, 22)
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23. A computer-readable medium having computer-executable instructions for identifying corresponding points among multiple images of a scene, said computer-executable instructions comprising:
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identifying interest points representing potential corresponding points in each image, wherein each interest point corresponds to a location in an image that is identifiable by a unique pattern formed by a prescribed property of the pixels in a neighborhood centered around the location; assigning an orientation to each interest point, wherein the orientation is derived from said pattern formed by the prescribed property of the pixels in the neighborhood centered around the interest point; generating a descriptor for each of the interest points which characterizes each point in a manner that is substantially invariant to changes in image location, orientation, and scale, as well as to changes in the bias and gain of the pixels used to define the location and orientation of the point; finding substantially matching descriptors among the images; and designating the interest points associated with each set of matching descriptors that appear in different images as corresponding points.
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Specification