Patents by Inventor Erik Learned-Miller

Erik Learned-Miller has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20250191364
    Abstract: A system for video anomaly detection is configured to extract, from a set of input frames of the input video, input appearance features indicative of the appearance of the object in a frame, input size features indicative of the size of the object in the scene, input location features indicative of the location of the object in the scene, and input trajectory features indicative of a trajectory of the object tracked in a set of frames of the input video. The system combines the input appearance features, the input size features, the input location features, and the input trajectory features to produce an input feature vector and compares the input feature vector with each of the exemplars extracted from the normal video to determine the smallest distance from the input feature vector to its closest exemplar. The system declares the anomaly when the smallest distance is greater than a threshold.
    Type: Application
    Filed: December 7, 2023
    Publication date: June 12, 2025
    Applicant: Mitsubishi Electric Research Laboratories, Inc.
    Inventors: Michael Jones, Ashish Singh, Erik Learned-Miller
  • Publication number: 20240185605
    Abstract: Embodiments of the present disclosure disclose a method and a system for video anomaly detection. The system is configured to collect a sequence of input video frames of an input video of a scene. In addition, the system is configured to partition each input video frame of the sequence of input video frames into a plurality of input video patches. Further, the system is configured to process each of the plurality of input video patches with one or more classifiers. Each of the one or more classifiers corresponds to a deep neural network trained to estimate one or more attributes of the plurality of input video patches from an output of a penultimate layer of the deep neural network. Furthermore, the system is configured to compare the output of the penultimate layer. The system is further configured to detect an anomaly based on the output of the penultimate layer.
    Type: Application
    Filed: December 5, 2022
    Publication date: June 6, 2024
    Inventors: Michael Jones, Ashish Singh, Erik Learned-Miller