Invention Grant
- Patent Title: Bootstrap unsupervised learning
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Application No.: US16711494Application Date: 2019-12-12
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Publication No.: US11275971B2Publication Date: 2022-03-15
- Inventor: Igal Raichelgauz , Karina Odinaev
- Applicant: Cortica Ltd.
- Applicant Address: IL Tel-Aviv
- Assignee: Cortica Ltd.
- Current Assignee: Cortica Ltd.
- Current Assignee Address: IL Tel-Aviv
- Agency: Reches Patents
- Main IPC: G06K9/00
- IPC: G06K9/00 ; G06K9/62 ; G06K9/46 ; G06N20/00 ; G06K9/20 ; G06T5/50 ; G06T7/246 ; G06T7/70 ; G06T3/40

Abstract:
Systems, and method and computer readable media that store instructions for motion based object detection. The method may include receiving or generating a video stream that comprises a sequence of images; generating image signatures of the images; wherein each image is associated with an image signature that comprises identifiers; wherein each identifier identifiers a region of interest within the image; generating movement information indicative of movements of the regions of interest within consecutive images of the sequence of images; searching, based on the movement information, for a first group of regions of interest that follow a first movement; wherein different first regions of interest are associated with different parts of an object; and linking between first identifiers that identify the first group of regions of interest.
Public/Granted literature
- US20200311431A1 Bootstrap Unsupervised Learning Public/Granted day:2020-10-01
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