Method and apparatus for finding feature correspondences between images captured in real-world environments
First Claim
1. A method of processing images captured from an environment, comprising the steps of:
- detecting features in a set of two or more source images;
tracking the features to two or more destination images that surround the two or more source images;
identifying potential correspondences between features from different source images that track to the same image and that satisfy a feature similarity metric; and
selecting a maximal set of corresponding features from among the potential correspondences to form a set of image feature that is globally consistent across the set of two or more source images.
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Abstract
Techniques for computing a globally consistent set of image feature correspondences across a wide range of viewpoints suitable for interactive walkthroughs and visualizations. The inventive approach takes advantage of the redundancy inherent in a dense set of images captured in a plane (or in higher dimensions, e.g., images captured in a volume, images captured over time, etc). The technique may detect features in a set of source images and track the features to neighboring images. When features track to the same position in the same image, they are flagged as potential correspondences. Among the potential correspondences, the technique selects the maximal set using a greedy graph-labeling algorithm (e.g., best-first order). Only correspondences that produce a globally consistent labeling are selected. After globalization is done, a set of features common to a group of images can be quickly found and used to warp and combine the images to produce an interpolated novel view of the environment.
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Citations
19 Claims
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1. A method of processing images captured from an environment, comprising the steps of:
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detecting features in a set of two or more source images; tracking the features to two or more destination images that surround the two or more source images; identifying potential correspondences between features from different source images that track to the same image and that satisfy a feature similarity metric; and selecting a maximal set of corresponding features from among the potential correspondences to form a set of image feature that is globally consistent across the set of two or more source images. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. Apparatus for processing images captured from an environment, comprising:
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a memory; and at least one processor coupled to the memory and operative to;
(i) detect features in a set of two or more source images;
(ii) track the features to destination images that surround the two or more source images;
(iii) identify potential correspondences between features from different source images that track to the same image and that satisfy a feature similarity metric; and
(iv) select a maximal set of corresponding features from among the potential correspondences to form a set of image feature that is globally consistent across the set of two or more source images. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17, 18)
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19. A computer program product for processing images captured from an environment, comprising a computer readable medium containing one or more computer programs which when executed by a computer processor implement the steps of:
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detecting features in a set of two or more source images; tracking the features to two or more destination images that surround the two or more source images; identifying potential correspondences between features from different source images that track to the same image and that satisfy a feature similarity metric; and selecting a maximal set of corresponding features from among the potential correspondences to form a set of image features that globally consistent across the set of two or more source images.
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Specification