Optimization of multi-label problems in computer vision
AssigneeMicrosoft Corporation
InventorsCarsten Rother, Victor Lempitsky, Andrew Blake
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Abstract
A method of labeling pixels in an image is described where the pixel label is selected from a set of three or more labels. The pixel labeling problem is reduced to a sequence of binary optimizations by representing the label value for each pixel as a binary word and then optimizing the value of each bit within the word, starting with the most significant bit. Data which has been learned from one or more training images is used in the optimization to provide information about the less significant bits within the word.
Claims20
A method of labeling pixels in an image for image segmentation, wherein each label is selected from a set comprising at least three labels, the method comprising:
- representing a label value at each pixel as a binary word, wherein each binary word comprises a plurality of bits arranged in order of significance;
- determining, using a computer, a value of a most significant bit for each pixel in the image using a binary optimizer and learned data;
- and
- repeating the determination for each bit for each pixel in order of decreasing significance to obtain a solution comprising a label for each pixel in the image.
A computer readable memory storing information to enable a computing device to perform a process, the computing device comprising a processor and a memory, the process comprising:
- representing a label value at each pixel in an image as a binary word, wherein each binary word comprises a plurality of bits arranged in order of significance;
- determining a value of a most significant bit for each pixel in the image using a binary optimizer and learned data;
- and
- repeating the determination for each bit for each pixel in order of decreasing significance to obtain a solution comprising a label for each pixel in the image.
A method of labeling each pixel in an image for image segmentation with one of a set of at least three labels, the method comprising:
- representing labels associated with each of the pixels in the image as binary words, each word comprising a plurality of bits arranged in order of decreasing significance;
- selecting a first bit level, comprising a most significant bit from each of the binary words and calculating, using a computer, the value of each of the bits in the first bit level using binary optimization and learned data relating to less significant bits in each word;
- selecting a next bit level, comprising a next most significant bit from each of the binary words and calculating the value of each of the bits in the selected next bit level using binary optimization and learned data relating to less significant bits in each word;
- and
- repeating the selection of a next bit level and the calculation of values of bits in the selected next bit level until the values of all bits in all binary words have been calculated to produce a fully labeled image.
Dependencies are inferred from the claim text.