Attention Maps

Systems and methods for managing visual allocation are provided herein that use models to determine states based on visual data and, based thereon, output feedback based on the determined states. Visual data is initially obtained by a visual allocation management system. The visual data includes eye image sequences of a person in a particular state, such as engaging in a task or activity. Visual features can be identified from the visual data, such that glance information including direction and duration can be calculated. The visual data, information derived therefrom, and/or other contextual data is input into the models, which correspond to states, to calculate probabilities that the particular state that the person is engaged in is one of the modeled states. Based on the state identified as having the highest probability, an optimal feedback, such as a warning or instruction, can be output to a connected devices, systems, or objects.

Researchers

Bryan Reimer / Joseph Coughlin / Bruce Mehler / Joonbum Lee / Andres Munoz Delgado / Linda Angell / Bobbie Seppelt

Departments: Center for Transportation and Logistics
Technology Areas: Artificial Intelligence (AI) and Machine Learning (ML) / Sensing & Imaging: Optical Sensing

  • systems and methods for providing visual allocation management
    United States of America | Granted | 10,902,331
  • systems and methods for providing visual allocation management
    United States of America | Granted | 11,688,203

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