公开(公告)号：US20210287391A1

公开(公告)日：2021-09-16

申请号：US17162863

申请日：2021-01-29

Applicant: SeeChange Technologies Limited

Inventor： Koki MITSUNAMI ,  Michael Andrew PALLISTER

IPC: G06T7/70 ,  G06T7/55 ,  G06T7/80 ,  G06T5/00 ,  G06K9/00

Abstract: A computer-implemented method comprises obtaining first data comprising a first collection of coordinate data representing a position, or positions, of a first group of one or more objects detected in a first frame of a scene and obtaining second data comprising a second collection of coordinate data representing a position, or positions, of a second group of one or more objects detected in a second frame of the scene, wherein the second frame represents a different view of the scene than the first frame. The method further comprises determining whether any of the first group of objects correspond to any of the second group of objects in the scene based on the first collection of coordinate data and the second collection of coordinate data, wherein the first frame and the second frame are obtained from image data captured from a single camera position.

公开(公告)号：US20230186601A1

公开(公告)日：2023-06-15

申请号：US17912238

申请日：2021-03-17

Applicant: SeeChange Technologies Limited

Inventor： Timothy David HARTLEY ,  David Charles MCCAFFREY ,  Michael Andrew PALLISTER ,  Nimesh Naresh PATEL

IPC: G06V10/764 ,  G06K7/14

CPC classification number: G06V10/764 ,  G06K7/1447

Abstract: Apparatus having model-based machine learning and inferencing logic for controlling object transfer, comprises: an image input component to receive image data derived from a captured image of an object; a captured image classifier to 5 generate a first classification of the object by activating a trained model to analyse the image data; an input component to receive an object identifier for the object; an object identification classifier to generate a second classification of the object according to the object identifier; matching logic to detect failure to reconcile the first and second classification; heuristic logic responsive to the matching logic to 10 determine a causal factor in the failure; and training logic, operable when the heuristic logic determines that a causal factor in the failure to reconcile is a deficient first classification, to provide model training input comprising the image data and the object identifier to the model-based machine learning logic.

公开(公告)号：US20230177391A1

公开(公告)日：2023-06-08

申请号：US17911558

申请日：2021-03-17

Applicant: SEECHANGE TECHNOLOGIES LIMITED

Inventor： David PACKWOOD ,  Michael Andrew PALLISTER ,  Ariel Edgar RUIZ-GARCIA ,  Nimesh Naresh PATEL ,  Eleftherios FANIOUDAKIS

IPC: G06N20/00

CPC classification number: G06N20/00

Abstract: Provided is machine learning apparatus comprising: a dataset for input to a training procedure of a machine learning model; data capture logic operable to capture from an object at least one datum for inclusion in the dataset; association logic operable to derive an additional characteristic of the object; annotator logic operable in response to the data capture logic and the association logic to create an annotation linking the additional characteristic with the at least one datum; storage logic operable to store the or each datum with an associated annotation in the dataset; and input logic to supply the dataset as machine learning input.