公开(公告)号：US20230070439A1

公开(公告)日：2023-03-09

申请号：US17794555

申请日：2021-03-18

Applicant: QUALCOMM Technologies, Inc.

Inventor： Deepak Kumar GUPTA ,  Efstratios GAVVES ,  Arnold Wilhelmus Maria SMEULDERS

IPC: G06T7/73 ,  G06T5/20

Abstract: A method for object tracking includes receiving a target image of an object of interest. Latent space features of the target image is modified at a forward pass for a neural network by dropping at least one channel of the latent space features, dropping a channel corresponding to a slice of the latent space features, or dropping one or more features of the latent space features. At the forward pass, a location of the object of interest in a search image is predicted based on the modified latent space features. The location of the object of interest is identified by aggregating predicted locations from the forward pass.

公开(公告)号：US20230036702A1

公开(公告)日：2023-02-02

申请号：US17756957

申请日：2020-12-14

Applicant: Qualcomm Technologies, Inc.

Inventor： Matthias REISSER ,  Max WELLING ,  Efstratios GAVVES ,  Christos LOUIZOS

IPC: G06N3/02

Abstract: Aspects described herein provide a method of processing data, including: receiving a set of global parameters for a plurality of machine learning models; processing data stored locally on an processing device with the plurality of machine learning models according to the set of global parameters to generate a machine learning model output; receiving, at the processing device, user feedback regarding machine learning model output for the plurality of machine learning models; performing an optimization of the plurality of machine learning models based on the machine learning output and the user feedback to generate locally updated machine learning model parameters; sending the locally updated machine learning model parameters to a remote processing device; and receiving a set of globally updated machine learning model parameters for the plurality of machine learning models.

公开(公告)号：US20200302185A1

公开(公告)日：2020-09-24

申请号：US16827342

申请日：2020-03-23

Applicant: QUALCOMM Technologies, Inc.

Inventor： Noureldien Mahmoud Elsayed HUSSEIN ,  Efstratios GAVVES ,  Arnold Wilhelmus Maria SMEULDERS

IPC: G06K9/00 ,  G06N3/04

Abstract: A method for classifying subject activities in videos includes learning latent (previously generated) concepts that are analogous to nodes of a graph to be generated for an activity in a video. The method also includes receiving video segments of the video. A similarity between the video segments and the previously generated concepts is measured to obtain segment representations as a weighted set of latent concepts. The method further includes determining a relationship between the segment representations and their transitioning pattern over time to determine a reduced set of nodes and/or edges for the graph. The graph of the activity in the video represented by the video segments is generated based on the reduced set of nodes and/or edges. The nodes of the graph are represented by the latent concepts. Subject activities in the video are classified based on the graph.

公开(公告)号：US20190147602A1

公开(公告)日：2019-05-16

申请号：US16186391

申请日：2018-11-09

Applicant: QUALCOMM Technologies, Inc.

Inventor： Ran TAO ,  Efstratios GAVVES ,  Arnold Wilhelmus Maria SMEULDERS

IPC: G06T7/246 ,  G06T7/73 ,  G06K9/62

Abstract: A method of tracking an object includes performing a hybrid search over a sequence of frames. The hybrid search includes periodically performing a global search on selected frames of the sequence of frames and performing a local search on frames between the selected frames of the global search. The method also includes updating a similarity function based on a result of the hybrid search. The method further includes tracking the object based on the hybrid search.