System and method for image analysis
First Claim
1. A method for image analysis, comprising:
- recording an image at a vehicle system mounted to a vehicle;
automatically detecting an object within the image with a first module;
automatically defining a first bounding box about the detected object;
modifying the image with the first bounding box for the detected object to generate a first modified image;
at a first verification module associated with the first module, labeling the first bounding box within the modified image as one of a false positive, a false negative, a true positive, and a true negative detected object;
training the first module with the label for the first bounding box;
automatically classifying the detected object with a second module, wherein classifying the detected object comprises automatically assigning an object class to the detected object, wherein the object class is one of a plurality of object classes, to generate a classified object;
modifying the image with a second bounding box for the classified object to generate a second modified image, wherein the second modified image comprises a set of pixels;
at a second verification module associated with the object class, labeling the second bounding box within the second modified image as one of a false positive, a false negative, a true positive, and a true negative for the object class, wherein the second verification module is one of a plurality of verification modules, each associated with a different object class of the plurality of object classes, wherein labeling the second bounding box comprises;
automatically determining a horizon in the second modified image based on image fiducials, andautomatically labeling the detected object as a false positive based on at least a portion of the second bounding box comprising pixels of the set of pixels located above the horizon;
training the second module with the label for the second bounding box within the second modified image; and
automatically detecting and classifying objects within a second image, recorded at the vehicle system, with the trained first module and trained second module, respectively.
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Accused Products
Abstract
A method for image analysis, including recording an image sequence at a vehicle system mounted to a vehicle; automatically detecting an object within the image sequence with a detection module; automatically defining a bounding box about the detected object within each image of the image sequence; modifying the image sequence with the bounding boxes for the detected object to generate a modified image sequence; at a verification module associated with the detection module, labeling the modified image sequence as comprising one of a false positive, a false negative, a true positive, and a true negative detected object based on the bounding box within at least one image of the modified image sequence; training the detection module with the label for the modified image sequence; and automatically detecting objects within a second image sequence recorded with the vehicle system with the trained detection module.
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Citations
17 Claims
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1. A method for image analysis, comprising:
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recording an image at a vehicle system mounted to a vehicle; automatically detecting an object within the image with a first module; automatically defining a first bounding box about the detected object; modifying the image with the first bounding box for the detected object to generate a first modified image; at a first verification module associated with the first module, labeling the first bounding box within the modified image as one of a false positive, a false negative, a true positive, and a true negative detected object; training the first module with the label for the first bounding box; automatically classifying the detected object with a second module, wherein classifying the detected object comprises automatically assigning an object class to the detected object, wherein the object class is one of a plurality of object classes, to generate a classified object; modifying the image with a second bounding box for the classified object to generate a second modified image, wherein the second modified image comprises a set of pixels; at a second verification module associated with the object class, labeling the second bounding box within the second modified image as one of a false positive, a false negative, a true positive, and a true negative for the object class, wherein the second verification module is one of a plurality of verification modules, each associated with a different object class of the plurality of object classes, wherein labeling the second bounding box comprises; automatically determining a horizon in the second modified image based on image fiducials, and automatically labeling the detected object as a false positive based on at least a portion of the second bounding box comprising pixels of the set of pixels located above the horizon; training the second module with the label for the second bounding box within the second modified image; and automatically detecting and classifying objects within a second image, recorded at the vehicle system, with the trained first module and trained second module, respectively. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A method for image analysis, comprising:
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recording an image sequence at a vehicle system mounted to a vehicle; automatically detecting an object within the image sequence with a detection module; automatically defining a bounding box about the detected object within each image of the image sequence; modifying the image sequence with the bounding boxes for the detected object to generate a modified image sequence; at a verification module associated with the detection module, labeling the modified image sequence as comprising one of a false positive, a false negative, a true positive, and a true negative detected object based on the bounding box within at least one image of the modified image sequence; training the detection module with the label for the modified image sequence; automatically detecting objects within a second image sequence recorded with the vehicle system with the trained detection module; automatically classifying the detected object with a classification module, wherein classifying the detected object comprises automatically assigning an object class to the detected object based on a vehicle context parameter determined at the vehicle system, wherein the object class is one of a plurality of object classes, to generate a classified object; modifying the image sequence with a second bounding box for the classified object within each image of the image sequence to generate a second modified image sequence; at a second verification module associated with the object class, labeling the second modified image sequence as comprising one of a false positive, a false negative, a true positive, and a true negative for the object class based on the second bounding box within at least one image of the second modified image sequence, wherein the second verification module is one of a plurality of verification modules, each associated with a different object class of the plurality of object classes; and training the classification module with the labels for the second bounding box within the second modified image sequence; and automatically classifying objects within the second image sequence recorded with the vehicle system with the trained classification module. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16, 17)
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Specification