FEATURE EXTRACTION FOR OBJECT RE-IDENTIFICATION OR OBJECT CLASSIFICATION USING A COMPOSITE IMAGE

    公开(公告)号:US20250005907A1

    公开(公告)日:2025-01-02

    申请号:US18734165

    申请日:2024-06-05

    Applicant: Axis AB

    Abstract: A method for feature extraction of detected objects, comprising the steps of: receiving a plurality of images, each depicting an object detected by the object detecting application; concatenating the plurality of images into a composite image according to a grid pattern; feeding the composite image through a convolutional neural network (CNN) trained for feature extraction, wherein each convolutional layer of the CNN is configured to, while convolving input data to the convolutional layer using a convolutional filter: determine a currently convolved image of the plurality of images by determining a centre coordinate of a subset of the input data currently covered by the convolutional filter, and mapping the centre coordinate to the grid pattern; and selectively nullifying all weights of the convolutional filter that cover input data derived from any of the plurality of images not being the currently convolved image.

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