System and process for bootstrap initialization of nonparametric color models
First Claim
1. A system for tracking at least one object in at least one sequential image, comprising:
- a general purpose computing device; and
a computer program comprising program modules executable by the computing device, wherein the computing device is directed by the program modules of the computer program to;
(a) generate a state estimate defining probabilistic configurations of each object for each sequential image;
(b) generate observations of pixel color for each sequential image;
(c) automatically learn a color-based object model using the state estimate and the observations, and without using any of known and predefined object contours; and
(d) automatically track each object using the learned color-based model with a color-based tracking function.
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Abstract
A system and process for automatically learning a reliable color-based tracking system is presented. The tracking system is learned by using information produced by an initial object model in combination with an initial tracking function to probabilistically determine the configuration of one or more target objects in a temporal sequence of images, and a data acquisition function for gathering observations relating to color in each image. The observations gathered by the data acquisition function include information that is relevant to parameters desired for a final color-based object model. A learning function then uses probabilistic methods to determine conditional probabilistic relationships between the observations and probabilistic target configuration information to learn a color-based object model automatically tailored to specific target objects. The learned object model is then used in combination with the final tracking function to probabilistically locate and track specific target objects in one or more sequential images.
25 Citations
44 Claims
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1. A system for tracking at least one object in at least one sequential image, comprising:
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a general purpose computing device; and
a computer program comprising program modules executable by the computing device, wherein the computing device is directed by the program modules of the computer program to;
(a) generate a state estimate defining probabilistic configurations of each object for each sequential image;
(b) generate observations of pixel color for each sequential image;
(c) automatically learn a color-based object model using the state estimate and the observations, and without using any of known and predefined object contours; and
(d) automatically track each object using the learned color-based model with a color-based tracking function. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14)
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15. A computer-implemented process for generating a color-based object model, comprising:
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generating a state estimate defining probabilistic states of an object for each of at least one sequential images;
generating observations of pixel color for each sequential image; and
automatically learning the color-based object model using the state estimates and the observations and without using any of known and predefined object contours. - View Dependent Claims (16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33)
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34. A computer-readable memory for identifying the configuration of objects of interest in a scene, comprising:
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a computer-readable storage medium; and
a computer program comprising program modules stored in the storage medium, wherein the storage medium is so configured by the computer program that it causes the computer to, generate an initial configuration estimate for objects of interest within the scene, identify pixel color information within the scene that is relevant to a learned color-based object model, automatically learn the color-based object model by determining probabilistic relationships between the initial configuration estimates and the pixel color information without using any of known and predefined object contours, and, generate a final configuration estimate for objects of interest in the scene by using the color-based object model in combination with a color-based tracking function. - View Dependent Claims (35, 36, 37, 38, 39, 40, 41, 42, 43)
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44-47. -47. (Cancelled)
Specification