Low- And High-Fidelity Classifiers Applied To Road-Scene Images
First Claim
1. A method comprising:
- processing an image with a low-fidelity classifier, the low-fidelity classifier trained to calculate a probability, for each of a plurality of zones of the image, that a zone of the image comprises an object;
identifying a probable zone having a high probability for comprising the object;
forward feeding the probable zone to a high-fidelity classifier, the high-fidelity classifier trained to confirm a presence of the object in the probable zone.
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Abstract
Disclosures herein teach applying a set of sections spanning a down-sampled version of an image of a road-scene to a low-fidelity classifier to determine a set of candidate sections for depicting one or more objects in a set of classes. The set of candidate sections of the down-sampled version may be mapped to a set of potential sectors in a high-fidelity version of the image. A high-fidelity classifier may be used to vet the set of potential sectors, determining the presence of one or more objects from the set of classes. The low-fidelity classifier may include a first Convolution Neural Network (CNN) trained on a first training set of down-sampled versions of cropped images of objects in the set of classes. Similarly, the high-fidelity classifier may include a second CNN trained on a second training set of high-fidelity versions of cropped images of objects in the set of classes.
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Citations
20 Claims
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1. A method comprising:
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processing an image with a low-fidelity classifier, the low-fidelity classifier trained to calculate a probability, for each of a plurality of zones of the image, that a zone of the image comprises an object; identifying a probable zone having a high probability for comprising the object; forward feeding the probable zone to a high-fidelity classifier, the high-fidelity classifier trained to confirm a presence of the object in the probable zone. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A system comprising:
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a vehicle; a camera affixed to the vehicle configured to capture an image of a scene surrounding the vehicle; and a processor in communication with the camera and programmable to execute instructions stored in non-transitory computer readable storage media, the instructions comprising; processing an image with a low-fidelity classifier, the low-fidelity classifier trained to calculate a probability, for each of a plurality of zones of the image, that a zone of the image comprises an object; identifying a probable zone having a high probability for comprising the object; forward feeding the probable zone to a high-fidelity classifier, the high-fidelity classifier trained to confirm a presence of the object in the probable zone. - View Dependent Claims (12, 13, 14, 15)
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16. A processor that is programmable to execute instructions stored in non-transitory computer readable storage media, the instructions comprising:
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processing an image with a low-fidelity classifier, the low-fidelity classifier trained to calculate a probability, for each of a plurality of zones of the image, that a zone of the image comprises an object; identifying a probable zone having a high probability for comprising the object; forward feeding the probable zone to a high-fidelity classifier, the high-fidelity classifier trained to confirm a presence of the object in the probable zone. - View Dependent Claims (17, 18, 19, 20)
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Specification