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1.
公开(公告)号:US20200380708A1
公开(公告)日:2020-12-03
申请号:US16425764
申请日:2019-05-29
Applicant: Avigilon Corporation
Inventor: Barry GRAVANTE , Pietro RUSSO , Mahesh SAPTHARISHI
IPC: G06T7/521 , G06T7/20 , H04N13/156 , H04N13/275
Abstract: Methods, systems, and techniques for generating two-dimensional (2D) and three-dimensional (3D) images and image streams. The images and image streams may be generated using active stereo cameras projecting at least one illumination pattern, or by using a structured light camera and a pair of different illumination patterns of which at least one is a structured light illumination pattern. When using an active stereo camera, a 3D image may be generated by performing a stereoscopic combination of a first set of images (depicting a first illumination pattern) and a 2D image may be generated using a second set of images (optionally depicting a second illumination pattern). When using a structured light camera, a 3D image may be generated based on a first image that depicts a structured light illumination pattern, and a 2D image may be generated from the first image and a second image that depicts a different illumination pattern.
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2.
公开(公告)号:US20200382765A1
公开(公告)日:2020-12-03
申请号:US16435042
申请日:2019-06-07
Applicant: Avigilon Corporation
Inventor: Barry GRAVANTE , Pietro RUSSO , Mahesh SAPTHARISHI
IPC: H04N13/286 , H04N13/254 , H04N13/156 , H04N13/239 , H04N13/296
Abstract: Methods, systems, and techniques for generating two-dimensional (2D) and three-dimensional (3D) images and image streams. The images and image streams may be generated using active stereo cameras projecting at least one illumination pattern, or by using a structured light camera and a pair of different illumination patterns of which at least one is a structured light illumination pattern. When using an active stereo camera, a 3D image may be generated by performing a stereoscopic combination of a first set of images (depicting a first illumination pattern) and a 2D image may be generated using a second set of images (optionally depicting a second illumination pattern). When using a structured light camera, a 3D image may be generated based on a first image that depicts a structured light illumination pattern, and a 2D image may be generated from the first image and a second image that depicts a different illumination pattern.
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公开(公告)号:US20190132557A1
公开(公告)日:2019-05-02
申请号:US16219607
申请日:2018-12-13
Applicant: Avigilon Corporation
Inventor: Mahesh SAPTHARISHI
CPC classification number: H04N7/181 , B64C39/024 , B64C2201/027 , B64C2201/108 , B64C2201/127 , G06K9/00221 , G06K9/0063 , G06K9/00771 , G06K9/4652 , H04N5/232 , H04N5/23216 , H04N5/23241 , H04N5/23293 , H04N5/23296 , H04N5/23299 , H04N7/185
Abstract: A video surveillance system having a plurality of aerial camera devices such as cameras on drones operable from a plurality of docking stations. Each station has a dock for receiving, charging, and controlling the aerial camera devices.
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公开(公告)号:US20190332901A1
公开(公告)日:2019-10-31
申请号:US16265731
申请日:2019-02-01
Applicant: Avigilon Corporation
Inventor: Moussa DOUMBOUYA , Yanyan HU , Kevin PIETTE , Pietro RUSSO , Mahesh SAPTHARISHI , Bo Yang YU
IPC: G06K9/62 , G06T7/20 , G06T7/593 , G06K9/00 , G08B21/18 , G01S13/04 , A61B5/01 , A61B5/08 , A61B5/00
Abstract: Methods, systems, and techniques for monitoring an object-of-interest within a region involve receiving at least data from two sources monitoring a region and correlating that data to determine that an object-of-interest depicted or represented in data from one of the sources is the same object-of-interest depicted or represented in data from the other source. Metadata identifying that the object-of-interest from the two sources is the same object-of-interest is then stored for later use in, for example, object tracking.
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公开(公告)号:US20190258885A1
公开(公告)日:2019-08-22
申请号:US16279975
申请日:2019-02-19
Applicant: Avigilon Corporation
Inventor: Kevin PIETTE , Pietro RUSSO , Mahesh SAPTHARISHI , Bo Yang YU
Abstract: Methods, systems, and techniques for classifying and/or detecting objects using visible and invisible light images. A visible light image and an invisible light image are received at a convolutional neural network (CNN). The visible light image depicts a region-of-interest imaged using visible light. The invisible light image depicts at least a portion of the region-of-interest imaged using invisible light, and at least one of the images depicts an object-of-interest within the portion of the region-of-interest shared between the images. The CNN then classifies and/or detects the object-of-interest using the images. The CNN may be trained to perform this classification and/or detection using pairs of visible and invisible light training images.
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公开(公告)号:US20190080722A1
公开(公告)日:2019-03-14
申请号:US16160882
申请日:2018-10-15
Applicant: Avigilon Corporation
Inventor: Moussa DOUMBOUYA , Mahesh SAPTHARISHI , Eric SJUE , Hannah VALBONESI
IPC: G11B27/22 , G06F3/0482 , G06F3/0484 , G06Q10/00 , G11B27/28 , H04N7/18 , G11B27/34 , G11B27/10 , G11B27/30 , G06T7/292
CPC classification number: G11B27/22 , G06F3/0482 , G06F3/04847 , G06Q10/00 , G06T7/292 , G06T7/74 , G06T2207/10016 , G06T2207/20076 , G06T2207/30196 , G06T2207/30232 , G06T2207/30241 , G11B27/102 , G11B27/28 , G11B27/3081 , G11B27/309 , G11B27/34 , H04N7/181 , H04N7/188
Abstract: A method, system and computer program product for interactively identifying same individuals or objects present in video recordings is disclosed. When a thumbnail in a set of thumbnails is selected, new information is obtained. The new information may be that an individual or object is present in the portion of the video recording associated with the thumbnail. A search can be carried out for the individual or object based on the new information. The search generates new match likelihoods for each of displayed thumbnails within a user interface page. The displayed thumbnails are re-ordered based on the new match likelihoods.
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7.
公开(公告)号:US20210051312A1
公开(公告)日:2021-02-18
申请号:US16539888
申请日:2019-08-13
Applicant: Avigilon Corporation
Inventor: Dharanish KEDARISETTI , Pietro RUSSO , Peter L. VENETIANER , Mahesh SAPTHARISHI
IPC: H04N13/268 , G06T15/40 , G06T7/50 , H04N13/239
Abstract: Methods, systems, and techniques for enhancing use of two-dimensional (2D) video analytics by using depth data. Two-dimensional image data representing an image comprising a first object is obtained, as well as depth data of a portion of the image that includes the first object. The depth data indicates a depth of the first object. An initial 2D classification of the portion of the image is generated using the 2D image data without using the depth data. The initial 2D classification is stored as an approved 2D classification when the initial 2D classification is determined consistent with the depth data. Additionally or alternatively, a confidence level of the initial 2D classification may be adjusted depending on whether the initial 2D classification is determined to be consistent with the depth data, or the depth data may be used with the 2D image data for classification.
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公开(公告)号:US20190130202A1
公开(公告)日:2019-05-02
申请号:US16172557
申请日:2018-10-26
Applicant: Avigilon Corporation
Inventor: Moussa DOUMBOUYA , Lu HE , Yanyan HU , Mahesh SAPTHARISHI , Hao ZHANG , Nicholas John ALCOCK , Roger David DONALDSON , Seyedmostafa AZIZABADIFARAHANI , Ken JESSEN
Abstract: There are described methods and systems for facilitating identification of an object-of-interest. A face similarity score and a body similarity score of a query image relative to a gallery image are determined. A fused similarity score of the query image relative to the gallery image is determined by applying a relationship between the face similarity score, the body similarity score, and the fused similarity score. The fused similarity score is indicative of whether or not the object-of-interest and the potential object-of-interest are the same object-of-interest. For example, a machine learning process is used to fuse the face similarity score and the body similarity into the fused similarity score. The process is repeated for multiple gallery images. The gallery images may then be ranked according to their respective fused similarity scores.
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