Distributive hierarchical model for object recognition in video
AssigneeUniversity of Florida Research Foundation, Inc.
InventorsRakesh Chalasani, Jose C. Principe
Life of this patent
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Abstract
Various examples are provided for object recognition in video. In one example, among others, a system includes processing circuitry including a processor. The processing circuitry is configured to process a sequence of images to recognize an object in the images, the recognition of the object based upon a hierarchical model. In another example, a method includes determining input data from a plurality of overlapping pixel patches of a video image; determining a plurality of corresponding states based at least in part upon the input data and an over-complete dictionary of filters; and determining a cause based at least in part upon the plurality of corresponding states. The cause may be used to identify an object in the video image.
Claims14
A system, comprising:
- processing circuitry including a processor, the processing circuitry configured to process a sequence of images to recognize an object in the sequence of images, the recognition of the object based upon a hierarchical model, where:
- a first level of the hierarchical model includes:
- a state estimator configured to determine state data associated with one image of the sequence of images based at least in part upon input data from the one image, the input data comprising a plurality of vectors associated with corresponding overlapping pixel patches extracted from the one image;
- and
- a parameter estimator configured to determine parameters of the state estimator of the first level based at least in part upon the input data from the one image;
- and
- a second level of the hierarchical model includes:
- a state estimator configured to determine state data associated with the one image based at least in part upon input data from the first level of the hierarchical model and provide a top-down prediction to the state estimator of the first level;
- and
- a parameter estimator configured to determine parameters of the state estimator of the second level based at least in part upon the input data from the first level.
A system, comprising:
- a first image processing layer of a hierarchical model, including:
- sparse inference input circuitry configured to determine a plurality of states based at least in part upon input data associated with a video image;
- and
- sparse inference output circuitry configured to determine a cause associated with the video image, the cause based at least in part upon the plurality of states determined by the sparse inference input circuitry of the first image processing layer;
- and
- a second image processing layer of the hierarchical model, including:
- sparse inference input circuitry configured to determine at least one state based at least in part upon input data comprising the cause determined by the sparse inference output circuitry of the first image processing layer;
- and
- sparse inference output circuitry configured to determine a second cause associated with the video image, the second cause based at least in part upon the at least one state determined by the sparse inference input circuitry of the second image processing layer;
- where the sparse inference output circuitry of the second image processing layer is configured to receive a top-down prediction from sparse inference output circuitry of a third image processing layer.
A method, comprising:
- determining input data from a plurality of overlapping pixel patches of a video image;
- determining a plurality of corresponding states based at least in part upon the input data associated with the video image and an over-complete dictionary of filters;
- determining a first cause associated with a first layer of a hierarchical model based at least in part upon the plurality of corresponding states;
- determining at least one state based at least in part upon input data comprising the first cause, where the first cause is modulated based upon a top-down prediction associated with a second cause associated with a second layer of the hierarchical model;
- and
- determining the second cause associated with the second layer of the hierarchical model, the second cause based at least in part upon the at least one state.
Dependencies are inferred from the claim text.