Method for automatically classifying images into events
First Claim
Patent Images
1. A method for automatically classifying images into events, the method comprising the steps of:
- (a) receiving a plurality of images having either or both date and/or time of image capture;
(b) determining one or more largest time differences of the plurality of images based on time and/or date clustering of the images; and
, (c) separating the plurality of images into the events based on having one or more boundaries between events which one or more boundaries correspond to the one or more largest time differences.
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Abstract
A method for automatically classifying images into events, the method includes the steps of: receiving a plurality of images having either or both date and/or time of image capture; determining one or more largest time differences of the plurality of images based on clustering of the images; and separating the plurality of images into the events based on having one or more boundaries between events which one or more boundaries correspond to the one or more largest time differences.
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Citations
8 Claims
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1. A method for automatically classifying images into events, the method comprising the steps of:
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(a) receiving a plurality of images having either or both date and/or time of image capture;
(b) determining one or more largest time differences of the plurality of images based on time and/or date clustering of the images; and
,(c) separating the plurality of images into the events based on having one or more boundaries between events which one or more boundaries correspond to the one or more largest time differences. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A method for automatically classifying images into events, the method comprising the steps of:
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(a) receiving a plurality of images having either or both date and/or time of image capture;
(b) determining one or more largest time differences of the plurality of images based on time and/or date clustering of the images;
(c) separating the plurality of images into the events based on having one or more boundaries between events which one or more boundaries correspond to the one or more largest time differences; and
(d) analyzing the events for content by dividing the images into a plurality of blocks and grouping the images into subject grouping based on block-based histogram correlation which includes computing a color histogram of each block and computing a histogram intersection value which determines the similarity between blocks, thereby refining and improving the overall classification and subject grouping of the events.
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Specification