Visual attention and segmentation system
First Claim
1. A vision system for object-based attention and segmentation, comprising a memory and one or more processors, the memory encoded with instructions to cause the system to include:
- a feature extraction module configured to receive an image representing a scene with an object in the scene and generate a feature map corresponding to receptive fields in the retina for red-center/green-surround, green-center/red-surround, blue-center/yellow-surround, bright-center/dark-surround, and dark-center/bright-surround;
a feature edge detection module configured to extract edge information from the feature map and generate an edge map, the edge map including incomplete boundaries and unclosed contours;
a watershed module configured to generate proto-objects based on the edge map;
a saliency module configured to compute a saliency of each proto-object and rank the proto-objects relative to other proto-objects in terms of their saliency; and
a region growing module configured to compute a feature boundary for the proto-object with the highest saliency and a list of pixels in the image that constitutes the proto-object feature boundary, and further configured to output the pixels confined by the feature boundary as an extracted object.
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Accused Products
Abstract
Described is a bio-inspired vision system for attention and object segmentation capable of computing attention for a natural scene, attending to regions in a scene in their rank of saliency, and extracting the boundary of an attended proto-object based on feature contours to segment the attended object. The attention module can work in both a bottom-up and a top-down mode, the latter allowing for directed searches for specific targets. The region growing module allows for object segmentation that has been shown to work under a variety of natural scenes that would be problematic for traditional object segmentation algorithms. The system can perform at multiple scales of object extraction and possesses a high degree of automation. Lastly, the system can be used by itself for stand-alone searching for salient objects in a scene, or as the front-end of an object recognition and online labeling system.
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Citations
27 Claims
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1. A vision system for object-based attention and segmentation, comprising a memory and one or more processors, the memory encoded with instructions to cause the system to include:
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a feature extraction module configured to receive an image representing a scene with an object in the scene and generate a feature map corresponding to receptive fields in the retina for red-center/green-surround, green-center/red-surround, blue-center/yellow-surround, bright-center/dark-surround, and dark-center/bright-surround; a feature edge detection module configured to extract edge information from the feature map and generate an edge map, the edge map including incomplete boundaries and unclosed contours; a watershed module configured to generate proto-objects based on the edge map; a saliency module configured to compute a saliency of each proto-object and rank the proto-objects relative to other proto-objects in terms of their saliency; and a region growing module configured to compute a feature boundary for the proto-object with the highest saliency and a list of pixels in the image that constitutes the proto-object feature boundary, and further configured to output the pixels confined by the feature boundary as an extracted object. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A computer program product for visual object-based attention and segmentation, the computer program product comprising computer-readable instruction means stored on a non-transitory computer-readable medium that are executable by a computer for causing the computer to:
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receive an image representing a scene and generate feature maps corresponding to receptive fields in the retina for red-center/green-surround, green-center/red-surround, blue-center/yellow-surround, bright-center/dark-surround, and dark-center/bright-surround; receive the feature maps and generate a master edge map using the feature maps; receive the master edge map and generate a plurality of watershed-regions, each watershed-region having a plurality of features; receive the plurality of watershed-regions and compute a plurality of saliencies corresponding to each watershed-region; select among the plurality of watershed-regions a most-salient-region; and receive the watershed-regions and grow the most-salient-region by joining neighboring watershed-regions to form a proto-object, the proto-object having a feature boundary; generate a list of pixels in the image that constitutes the proto-object feature boundary; and output the pixels confined by the feature boundary as an extracted object. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17, 18)
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19. A method for bio-inspired visual object-based attention and segmentation comprising acts of:
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receiving an image representing a scene and generating feature maps corresponding to receptive fields in the retina for red-center/green-surround, green-center/red-surround, blue-center/yellow-surround, bright-center/dark-surround, and dark-center/bright-surround; receiving the feature maps and generating a master edge map using to the feature maps; receiving the master edge map and generating a plurality of watershed-regions, each watershed-region having a plurality of features; receiving the plurality of watershed-regions and computing a plurality of saliencies corresponding to each watershed-region; selecting among the plurality of watershed-regions a most-salient-region; and receiving the watershed-regions and growing the most-salient-region by joining neighboring watershed-regions to form a proto-object, the proto-object having a feature boundary; generating a list of pixels in the image that constitutes the proto-object feature boundary; and outputting the pixels confined by the feature boundary as an extracted object. - View Dependent Claims (20, 21, 22, 23, 24, 25, 26, 27)
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Specification