Abstract: A robotic arm mounted camera system allows an end-user to begin using the camera for object recognition without involving a robotics specialist. Automated object model calibration is performed under conditions of variable robotic arm pose dependent feature recognition of an object. The user can then teach the system to perform tasks on the object using the calibrated model. The camera's body can have parallel top and bottom sides and adapted to be fastened to a robotic arm end and to an end effector with its image sensor and optics extending sideways in the body, and it can include an illumination source for lighting a field of view.

Abstract: A robotic arm mounted camera system allows an end-user to begin using the camera for object recognition without involving a robotics specialist. Automated object model calibration is performed under conditions of variable robotic arm pose dependent feature recognition of an object. The user can then teach the system to perform tasks on the object using the calibrated model. The camera's body can have parallel top and bottom sides and adapted to be fastened to a robotic arm end and to an end effector with its image sensor and optics extending sideways in the body, and it can include an illumination source for lighting a field of view.

Abstract: The technology is directed to determining a class associated with an image. In some examples, a method determines the class associated with an image. The method can include determining a segmentation score for an image segment based on a comparison of the image segment and a region of an image. The region of the image can be associated with the image segment. The method further includes determining a confidence score for the image segment based on the segmentation score and a classification score. The classification score can be indicative of a similarity between the image segment and at least one class. The method further includes determining a class associated with the image based on the confidence score. The method further includes outputting the class associated with the image.

Abstract: The technology is directed to determining a class associated with an image. In some examples, a method determines the class associated with an image. The method can include determining a segmentation score for an image segment based on a comparison of the image segment and a region of an image. The region of the image can be associated with the image segment. The method further includes determining a confidence score for the image segment based on the segmentation score and a classification score. The classification score can be indicative of a similarity between the image segment and at least one class. The method further includes determining a class associated with the image based on the confidence score. The method further includes outputting the class associated with the image.