Object detection approach using generative sparse, hierarchical networks with top-down and lateral connections for combining texture/color detection and shape/contour detection
First Claim
1. A computer-implemented method, comprising:
- producing, by a computing system, a first independent representation of objects in an image dataset using a color/texture detection algorithm;
producing, by the computing system, a second independent representation of objects in the image dataset using a shape/contour detection algorithm; and
combining, by the computing system, the first and second independent representations into a single coherent output using a combinatorial algorithm, wherein the first independent representation of objects and the second independent representation of objects are independent from one another,wherein the combining of the first and second independent representations into the single coherent output using the combinatorial algorithm comprises;
formatting, by the computing system, the first representation and the second representation as points in a matrix a size of a video frame of the image dataset;
forming, by the computing system, clusters based on hits that are within a predetermined proximity and of a same label; and
finding, by the computing system, a minimum volume enclosing ellipsoid to get an appropriate size and orientation of a bounding box.
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Accused Products
Abstract
An approach to detecting objects in an image dataset may combine texture/color detection, shape/contour detection, and/or motion detection using sparse, generative, hierarchical models with lateral and top-down connections. A first independent representation of objects in an image dataset may be produced using a color/texture detection algorithm. A second independent representation of objects in the image dataset may be produced using a shape/contour detection algorithm. A third independent representation of objects in the image dataset may be produced using a motion detection algorithm. The first, second, and third independent representations may then be combined into a single coherent output using a combinatorial algorithm.
18 Citations
18 Claims
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1. A computer-implemented method, comprising:
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producing, by a computing system, a first independent representation of objects in an image dataset using a color/texture detection algorithm; producing, by the computing system, a second independent representation of objects in the image dataset using a shape/contour detection algorithm; and combining, by the computing system, the first and second independent representations into a single coherent output using a combinatorial algorithm, wherein the first independent representation of objects and the second independent representation of objects are independent from one another, wherein the combining of the first and second independent representations into the single coherent output using the combinatorial algorithm comprises; formatting, by the computing system, the first representation and the second representation as points in a matrix a size of a video frame of the image dataset; forming, by the computing system, clusters based on hits that are within a predetermined proximity and of a same label; and finding, by the computing system, a minimum volume enclosing ellipsoid to get an appropriate size and orientation of a bounding box. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. A computer program embodied on a non-transitory computer-readable medium, the program configured to cause at least one processor to:
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produce a first independent representation of objects in an image dataset using a color/texture detection algorithm; produce a second independent representation of objects in the image dataset using a shape/contour detection algorithm; produce a third independent representation of objects in the image dataset using a motion detection algorithm; and combine the first, second, and third independent representations into a single coherent output using a combinatorial algorithm, wherein the first independent representation of objects, the second independent representation of objects, and the third independent representation of objects are independent from one another, wherein the combining of the first, second, and third independent representations into the single coherent output using the combinatorial algorithm comprises; formatting, by the computing system, the first, second, and third representations as points in a matrix a size of a video frame of the image dataset; forming, by the computing system, clusters based on hits that are within a predetermined proximity and of a same label; and finding, by the computing system, a minimum volume enclosing ellipsoid to get an appropriate size and orientation of a bounding box. - View Dependent Claims (15, 16)
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17. An apparatus, comprising:
- memory storing computer program instructions; and
at least one processor configured to execute the computer program instructions, the at least one processor configured to;combine a first independent representation of objects in an image dataset produced by a color/texture detection algorithm and a second independent representation of objects in the image dataset produced by a shape/contour detection algorithm into a single coherent output using a combinatorial algorithm, wherein the first independent representation of objects and the second independent representation of objects are independent from one another, wherein the combining of the first and second independent representations into the single coherent output using the combinatorial algorithm comprises; formatting, by the computing system, the first representation and the second representation as points in a matrix a size of a video frame of the image dataset; forming, by the computing system, clusters based on hits that are within a predetermined proximity and of a same label; and finding, by the computing system, a minimum volume enclosing ellipsoid to get an appropriate size and orientation of a bounding box. - View Dependent Claims (18)
- memory storing computer program instructions; and
Specification