Salient Object Segmentation
First Claim
1. A method implemented at least partially by a processor, the method comprising:
- receiving an input image that includes a salient object;
segmenting the input image into multiple regions;
calculating a saliency value for each of the segmented regions based on scale image levels;
constructing saliency maps based at least in part on the calculated saliency value for each of the segmented regions, the saliency maps to be constructed for the scale image levels;
constructing a total saliency map by combining the saliency maps constructed for the scale image levels;
connecting a set of line segments that are computed from the input image and utilizing the total saliency map to define a shape prior that has a defined boundary; and
extracting the salient object from the total saliency map and the shape prior.
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Accused Products
Abstract
Techniques for identifying a salient object with respect to its context are described. A process receives an input image that includes a salient object. The process segments the input image into multiple regions and calculates a saliency value for each of the segmented regions based on scale image levels. The process constructs saliency maps based at least in part on the calculated saliency value, and combines the saliency maps to construct a total saliency map. Next, the process connects a set of line segments computed from the input image and utilizes the total saliency map to compute a closed boundary, which forms a shape prior from the closed boundary, and extracts the salient object from the total saliency map and the shape prior.
37 Citations
20 Claims
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1. A method implemented at least partially by a processor, the method comprising:
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receiving an input image that includes a salient object; segmenting the input image into multiple regions; calculating a saliency value for each of the segmented regions based on scale image levels; constructing saliency maps based at least in part on the calculated saliency value for each of the segmented regions, the saliency maps to be constructed for the scale image levels; constructing a total saliency map by combining the saliency maps constructed for the scale image levels; connecting a set of line segments that are computed from the input image and utilizing the total saliency map to define a shape prior that has a defined boundary; and extracting the salient object from the total saliency map and the shape prior. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. One or more computer-readable storage media encoded with instructions that, when executed by one or more processors, cause the one or more processors to perform acts comprising:
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receiving an input image that includes a salient object; fragmenting the input image into multiple regions to create a saliency map; calculating a saliency; and forming a defined boundary with a set of line segments from the input image to define a shape prior. - View Dependent Claims (11, 12, 13, 14, 15)
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16. A system comprising:
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a memory; one or more processors coupled to the memory; an object application module executed on the one or more processors to receive an input image that includes a salient object; a saliency map module executed on the one or more processors to construct a saliency map by fragmenting the input image into multiple regions, the saliency map module executed on the one or more processor to calculate a saliency value for each region by computing a color difference between a region and neighboring regions, the saliency value of each region being weighted by Gaussian falloff weight that measures a distance of the region to an image center; and the object application module executed on the one or more processors to propagate the saliency value for each region to pixels. - View Dependent Claims (17, 18, 19, 20)
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Specification