Salient Object Detection
AssigneeMicrosoft Corporation
InventorsJian Sun, Tie Liu, Xiaoou Tang, Heung-Yeung Shum
Life of this patent
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Abstract
Methods for detecting a salient object in an input image are described. For this, the salient object in an image may be defined using a set of local, regional, and global features including multi-scale contrast, center-surround histogram, and color spatial distribution. These features are optimally combined through conditional random field learning. The learned conditional random field is then used to locate the salient object in the image. The methods can also use image segmentation, where the salient object is separated from the image background.
Claims20
A method for salient object detection in an image comprising:
- receiving the image that includes the salient object and a background;
- defining the salient object using various feature maps;
- combining the various feature maps of the salient object;
- and
- detecting the salient object using the combined features.
A method for conditional random field learning for salient object detection comprising:
- collecting a number of images of salient objects, from a variety of sources, wherein each of the images are labeled;
- computing a saliency probability map for each of the images;
- computing labeling consistency statistics for each of the images;
- selecting consistent images from the labeled images;
- determining feature maps for selected consistent images;
- and
- training conditional random fields for the conditional random field learning, using the feature maps.
A method for salient object detection in an image comprising:
- receiving the image that includes the salient object;
- resealing the image to standard size;
- defining local, regional, and global features of the image;
- and
- detecting the salient object by learned conditional random field.
Dependencies are inferred from the claim text.