System and method for road sign ground truth construction with a knowledge graph and machine learning
AssigneeRobert Bosch GmbH
InventorsJi Eun KIM, Wan-Yi LIN, Cory HENSON, Anh Tuan TRAN, Kevin H. HUANG
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Abstract
A method of road sign classification utilizing a knowledge graph, including detecting and selecting a representation of a sign across a plurality of frames, outputting a prompt initiating a request for a classification associated with the representation of the sign, classifying one or more images including the sign, querying the knowledge graph to obtain a plurality of road sign classes with at least one same attribute as the sign, and classifying the sign across the plurality of frames in response to a confidence level exceeding a threshold.
Claims20
A system comprising:
- an input interface configured to receive one or more images;
- a controller in communication with the input interface and configured to:
- detect and select a road sign identified across a plurality of frames from the one or more images;
- output a prompt initiating a request for a classification of the road sign;
- detect and classify one or more images including the road signs utilizing a machine learning model;
- query a knowledge graph to obtain a plurality of road sign classes with a same attribute as candidate classes for a next classifier;
- classify the road sign across the plurality of frames;
- and
- track the road sign across the plurality of frames.
A method of road sign classification utilizing a knowledge graph, comprising:
- detecting and selecting a representation of a sign across a plurality of frames;
- outputting a prompt initiating a request for a classification associated with the representation of the sign;
- classifying one or more images including the sign;
- querying the knowledge graph to obtain a plurality of road sign classes with at least one same attribute as the sign;
- and
- classifying the sign across the plurality of frames in response to a confidence level exceeding a threshold.
A system for road sign classification utilizing a machine learning model, comprising:
- a display configured to output a user interface;
- and
- a processor in communication with the display, the processor programmed to:
- detect and select a representation of a sign across one or more images utilizing the machine learning model;
- output a prompt at the user interface initiating a request for a classification associated with the representation of the sign;
- classify one or more images including the sign;
- obtain a plurality of road sign classes associated with candidates including at least one same attribute as the sign;
- and
- classify the sign across the one or more images in response to a confidence level exceeding a threshold.
Dependencies are inferred from the claim text.