System and method for predicting shoe traction using computer vision
AssigneeUniversity of Pittsburgh—Of the Commonwealth System of Higher Education
InventorsGerard ARISTIZÁBAL PLA, Kurt E. BESCHORNER
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Abstract
In one embodiment, a method includes accessing an image depicting a portion of a shoe and a background of the shoe, segmenting the portion of the shoe from the background by machine-learning models, extracting features configured for traction prediction by the machine-learning models, and determining a traction performance associated with the shoe based on the extracted feature by the machine-learning models.
Claims20
A method comprising, by one or more computing systems:
- accessing an image depicting a portion of a shoe and a background of the shoe;
- segmenting, by one or more machine-learning models, the portion of the shoe from the background;
- extracting, by the machine-learning models, a plurality of features configured for traction prediction;
- and
- determining, based on the extracted feature by the one or more machine-learning models, a traction performance associated with the shoe.
One or more computer-readable non-transitory storage media embodying software that is operable when executed to:
- access an image depicting a portion of a shoe and a background of the shoe;
- segment, by one or more machine-learning models, the portion of the shoe from the background;
- extract, by the machine-learning models, a plurality of features configured for traction prediction;
- and
- determine, based on the extracted feature by the one or more machine-learning models, a traction performance associated with the shoe.
A system comprising:
- one or more processors;
- and a non-transitory memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to:
- access an image depicting a portion of a shoe and a background of the shoe;
- segment, by one or more machine-learning models, the portion of the shoe from the background;
- extract, by the machine-learning models, a plurality of features configured for traction prediction;
- and
- determine, based on the extracted feature by the one or more machine-learning models, a traction performance associated with the shoe.
Dependencies are inferred from the claim text.