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US Patent 10133933 Item put and take detection using image recognition

Patent 10133933 was granted and assigned to Standard Cognition, Corp. on November, 2018 by the United States Patent and Trademark Office.

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Patent abstractTimelineTable: Further ResourcesReferences
Is a
Patent
Patent
1

Patent attributes

Current Assignee
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Standard Cognition, Corp.
1
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
1
Patent Number
101339331
Patent Inventor Names
Juan C. Lasheras1
Daniel L. Fischetti1
John F. Novak1
Jordan E. Fisher1
Kenneth S. Kihara1
Kyle E. Dorman1
Brandon L. Ogle1
Date of Patent
November 20, 2018
1
Patent Application Number
159071121
Date Filed
February 27, 2018
1
Patent Citations
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US Patent 10055853 Subject identification and tracking using image recognition
Patent Citations Received
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US Patent 11482045 Associating events with actors using digital imagery and machine learning
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US Patent 11488103 Customized retail environments
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US Patent 11501537 Multiple-factor verification for vision-based systems
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US Patent 11501453 Sensor array for scalable position tracking system
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US Patent 11501454 Mapping wireless weight sensor array for item detection and identification
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US Patent 11501455 System and method for position tracking using edge computing
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US Patent 11507933 Cashier interface for linking customers to virtual data
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US Patent 12131516 Reducing a search space for item identification using machine learning
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Patent Primary Examiner
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Anner N Holder
1
Patent abstract

Systems and techniques are provided for tracking puts and takes of inventory items by subjects in an area of real space. A plurality of cameras with overlapping fields of view produce respective sequences of images of corresponding fields of view in the real space. A processing system is coupled to the system. In one embodiment, the processing system comprises image recognition engines receiving corresponding sequences of images from the plurality of cameras. The image recognition engines process the images in the corresponding sequences to identify subjects represented in the images and generate classifications of the identified subjects. The system processes the classifications of identified subjects for sets of images in the sequences of images to detect takes and puts of inventory items on shelves by identified subjects.

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