Patent Document ID: 9449220
Application ID: 14257267

Base Claim:
1. A method for detecting cookware, the method comprising: identifying, by one or more computing devices, one or more locations respectively associated with one or more burners included in a cooktop, wherein identifying, by one or more computing devices, the one or more locations respectively associated with the one or more burners comprises: obtaining, by the one or more computing devices, a reference frame of imagery depicting the cooktop without any objects placed thereon; obtaining, by the one or more computing devices, one or more calibration frames of imagery depicting the cooktop with one or more items of cookware respectively positioned at the one or more locations respectively associated with the one or more burners, wherein the one or more calibration frames of imagery are captured when motion is not detected at the cooktop; performing, by the one or more computing devices, background subtraction for at least one of the one or more calibration frames of imagery with respect to the reference frame of imagery to identify new imagery; and segmenting, by the one or more computing devices, the new imagery to identify the one or more locations respectively associated with the one or more burners included in the cooktop; obtaining, by the one or more computing devices, a frame of imagery captured by a vision sensor, wherein the frame of imagery either depicts cookware on the cooktop, or does not depict cookware on the cooktop; segmenting, by the one or more computing devices, the frame of imagery into one or more image segments based at least in part on the one or more locations respectively associated with the one or more burners included in the cooktop; using, by the one or more computing devices, a classifier to provide an initial classification for each of the one or more image segments of the frame of imagery, the initial classification for each of the one or more image segments classifying the one or more image segments into either a first class of images depicting cookware or a second class of images not depicting cookware, wherein classification of one of the one or more image segments into the first class of images corresponds to detection of cookware on the cooktop; providing, by the one or more computing devices for at least one of the one or more image segments, an indication to a user of whether the initial classification for such image segment comprises the first class or the second class; after providing the indication for at least one of the one or more image segments, receiving, by the one or more computing devices, a user input indicating whether the initial classification for such image segment is correct; and when the user input indicates that the initial classification for one of the one or more image segments is not correct, changing, by the one or more computing devices, the initial classification for such image segment to a subsequent classification, wherein the subsequent classification comprises the second class when the initial classification comprises the first class, and wherein the subsequent classification comprises the first class when the initial classification comprises the second class.

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Claim 7:
7. The method of claim 1 , further comprising, prior to using, by the one or more computing devices, the classifier to provide the initial classification for each of the one or more image segments: obtaining, by the one or more computing devices, a first plurality of images captured by the vision sensor, wherein the first plurality of images depict cookware upon the cooktop; storing, by the one or more computing devices, the first plurality of images in a memory as a positive image training dataset; obtaining, by the one or more computing devices, a second plurality of images captured by the vision sensor, wherein the second plurality of images do not depict cookware upon the cooktop; storing, by the one or more computing devices, the second plurality of images in the memory as a negative image training dataset; and training, by the one or more computing devices, the classifier based at least in part on the positive image training dataset and the negative image training dataset.