Intelligent video thumbnail selection and generation
First Claim
1. A method for recommending a thumbnail image representative of a collection of images, the method comprising:
- computing a relevancy metric for each image of the collection of images, wherein the relevancy metric is computed based on at least one image characteristic selected from the group consisting of;
a size of a face in the image, wherein the relevancy metric is influenced in a first direction more when the face is large than when the face is small;
a number of eyes in the image, wherein the relevancy metric is influenced in the first direction more when the number of eyes is large than when the number of eyes is small;
a number of open eyes in the image, wherein the relevancy metric is influenced in the first direction more when the number of open eyes is large than when the number of open eyes is small;
an object or face in the image, wherein the relevancy metric is influenced in the first direction more when the object or face is identified as corresponding to a database entry than when the object or face is unidentified;
a computed brightness for the image, wherein the relevancy metric is influenced in the first direction more for brightness values within a predetermined brightness range than for brightness values outside of the predetermined brightness range;
a number of skin-colored pixels in the image, wherein the relevancy metric is influenced in the first direction more when the number of skin-colored pixels is large than when the number of skin-colored pixels is small;
identifying a subset of the collection of images that each have a relevancy metric influenced in the first direction by an amount that satisfies a predetermined threshold; and
transmitting for presentation through a user interface the identified subset of the collection of images.
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Abstract
In accordance with one embodiment, an intelligent video thumbnail selection and generation tool may select a relevant and visually stimulating image from a video file and generate a thumbnail including the image. The image may be selected by computing a relevancy metric for an image in the file based on one or more selected relevant features, and comparing that relevancy metric with the metric of at least one other image in the file. In another embodiment, a series of images in a video file may be divided into shots. One of the shots may be selected based on a shot relevancy metric and a key image from the shot may be selected as a thumbnail based on a key image relevancy metric, where the shot relevancy metric and the key image relevancy metrics may be computed based on one or more relevant content features.
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Citations
20 Claims
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1. A method for recommending a thumbnail image representative of a collection of images, the method comprising:
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computing a relevancy metric for each image of the collection of images, wherein the relevancy metric is computed based on at least one image characteristic selected from the group consisting of; a size of a face in the image, wherein the relevancy metric is influenced in a first direction more when the face is large than when the face is small; a number of eyes in the image, wherein the relevancy metric is influenced in the first direction more when the number of eyes is large than when the number of eyes is small; a number of open eyes in the image, wherein the relevancy metric is influenced in the first direction more when the number of open eyes is large than when the number of open eyes is small; an object or face in the image, wherein the relevancy metric is influenced in the first direction more when the object or face is identified as corresponding to a database entry than when the object or face is unidentified; a computed brightness for the image, wherein the relevancy metric is influenced in the first direction more for brightness values within a predetermined brightness range than for brightness values outside of the predetermined brightness range; a number of skin-colored pixels in the image, wherein the relevancy metric is influenced in the first direction more when the number of skin-colored pixels is large than when the number of skin-colored pixels is small; identifying a subset of the collection of images that each have a relevancy metric influenced in the first direction by an amount that satisfies a predetermined threshold; and transmitting for presentation through a user interface the identified subset of the collection of images. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 20)
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10. One or more computer-readable storage media of a tangible article of manufacture encoding computer-executable instructions for executing on a computer system a computer process, the computer process comprising:
selecting at least one image from a collection of images to be a selected image based on at least one image characteristic selected from the group consisting of; a size of a face in the image, wherein an image of the collection is more likely to be the selected image when the size of the face is large than when the size of the face is small; a number of eyes in the image, wherein an image of the collection is more likely to be the selected image when the number of eyes is large than when the number of eyes is small; a number of “
skin-colored”
pixels in the image, wherein an image of the collection is more likely to be the selected image when the number of skin-colored pixels is large than when the number of skin-colored pixels is small;a computed brightness for the image, wherein the relevancy metric is influenced in the first direction more for brightness values within a predetermined brightness range than for brightness values outside of the predetermined brightness range; an object or face in the image, wherein an image of the collection is more likely to be the selected image when the object or face is identified as corresponding to a database entry than when the object or face is unidentified; and a number of open eyes in the first targeted image, wherein an image of the collection is more likely to be the selected image when the number of open eyes is large than when the number of open eyes is small. - View Dependent Claims (11, 12, 13, 14)
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15. A system comprising:
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memory; a module stored in the memory and executable by a processor, the module configured to; compute a relevancy metric for each image of a collection of images based on an image characteristic selected from the group consisting of; a size of a face in the image, wherein the relevancy metric is influenced in a first direction more when the face is large than when the face is small; a number of eyes in the image, wherein the relevancy metric is influenced in the first direction more when the number of eyes is large than when the number of eyes is small; a number of open eyes in the image, wherein the relevancy metric is influenced in the first direction more when the number of open eyes is large than when the number of open eyes is small; an object or face in the image, wherein the relevancy metric is influenced in the first direction more when the object or face is identified as corresponding to a database entry than when then object or face is unidentified; a computed brightness for the image, wherein the relevancy metric is influenced in the first direction more for brightness values within a predetermined brightness range than for brightness values outside of the predetermined brightness range; a number of skin-colored pixels in the image, wherein the relevancy metric is influenced in the first direction more when the number of skin-colored pixels is large than when the number of skin-colored pixels is small; identify a subset of the collection of images, the subset including images that each have a relevancy metric influenced in the first direction by an amount that satisfies a predetermined threshold; transmit for presentation through a user interface the identified subset of one or more images. - View Dependent Claims (16, 17, 18, 19)
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Specification