SYSTEM AND METHOD FOR LANGUAGE-GUIDED VIDEO ANALYTICS AT THE EDGE

    公开(公告)号:US20220086401A1

    公开(公告)日:2022-03-17

    申请号:US17224304

    申请日:2021-04-07

    Abstract: Training a classifier using embeddings and building a latent space is disclosed. The embeddings may be based on weights in a trained machine learning model. Also, operation of the classifier to process video segments in real-time using the using the weights and the latent space is disclosed. The embeddings and the latent space allow the classification to be performed at an overall reduced dimensionality. The latent space is designed to efficiently scale with an increasing number of queries to permit fast search through the space. Embodiments permit real-time operation on video with dynamic features. The classifier reduces the bandwidth demand of video camera-equipped devices at a network edge by setting aside, accurately, non-informative video sequences rather than uploading video too many things over the network. Applications include security cameras, robots and augmented reality glasses.

    METHOD OF PROCESSING MULTIMODAL RETRIEVAL TASKS, AND AN APPARATUS FOR THE SAME

    公开(公告)号:US20230237089A1

    公开(公告)日:2023-07-27

    申请号:US18099711

    申请日:2023-01-20

    CPC classification number: G06F16/538 G06F16/2455

    Abstract: A method for multimodal content retrieval, may include: receiving a search query corresponding to a request for content; aggregating word features extracted from the search query based on a first set of learned weights; aggregating region features extracted from each of a plurality of images, based on a second set of learned weights, independently of the word features; computing a similarity score between the aggregated words features and the aggregated region features for each of the plurality of images; selecting candidate images from the plurality of images based on the similarity scores between each of the plurality of images and the search query; and selecting at least one final image from the candidate images as a response to the search query, based on attended similarity scores of the candidate images with respect to the search query.

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