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1. WO2020197902 - GROUPING STROKES OF DIGITAL INK

Publication Number WO/2020/197902
Publication Date 01.10.2020
International Application No. PCT/US2020/023474
International Filing Date 19.03.2020
IPC
G06F 3/0488 2013.01
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
FELECTRIC DIGITAL DATA PROCESSING
3Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
01Input arrangements or combined input and output arrangements for interaction between user and computer
048Interaction techniques based on graphical user interfaces
0487using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser
0488using a touch-screen or digitiser, e.g. input of commands through traced gestures
G06K 9/00 2006.01
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
9Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
CPC
G06F 3/04883
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
FELECTRIC DIGITAL DATA PROCESSING
3Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
01Input arrangements or combined input and output arrangements for interaction between user and computer
048Interaction techniques based on graphical user interfaces [GUI]
0487using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser
0488using a touch-screen or digitiser, e.g. input of commands through traced gestures
04883for entering handwritten data, e.g. gestures, text
G06K 9/00416
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
9Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
00402Recognising digital ink, i.e. recognising temporal sequences of handwritten position coordinates
00409Preprocessing; Feature extraction
00416Sampling; contour coding; stroke extraction
G06K 9/00422
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
9Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
00402Recognising digital ink, i.e. recognising temporal sequences of handwritten position coordinates
00422Matching; classification
G06K 9/2072
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
9Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
20Image acquisition
2054Selective acquisition/locating/processing of specific regions, e.g. highlighted text, fiducial marks, predetermined fields, document type identification
2072based on positionally close symbols, e.g. amount sign or URL-specific characters
G06K 9/222
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
9Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
20Image acquisition
22using hand-held instruments
222the instrument generating sequences of position coordinates corresponding to handwriting; preprocessing or recognising digital ink
G06K 9/6253
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
9Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
62Methods or arrangements for recognition using electronic means
6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
6253User interactive design
Applicants
  • MICROSOFT TECHNOLOGY LICENSING, LLC [US]/[US]
Inventors
  • ROUAIX, Francois M.
  • YANOWITZ, Eric
Agents
  • MINHAS, Sandip S.
  • ADJEMIAN, Monica
  • BARKER, Doug
  • CHATTERJEE, Aaron C.
  • CHEN, Wei-Chen Nicholas
  • CHOI, Daniel
  • CHURNA, Timothy
  • DINH, Phong
  • EVANS, Patrick
  • GABRYJELSKI, Henry
  • GUPTA, Anand
  • HINOJOSA-SMITH, Brianna L.
  • HWANG, William C.
  • JARDINE, John S.
  • LEE, Sunah
  • LEMMON, Marcus
  • MARQUIS, Thomas
  • MEYERS, Jessica
  • ROPER, Brandon
  • SPELLMAN, Steven
  • SULLIVAN, Kevin
  • SWAIN, Cassandra T.
  • WALKER, Matt
  • WIGHT, Stephen A.
  • WISDOM, Gregg
  • WONG, Ellen
  • WONG, Thomas S.
  • ZHANG, Hannah
  • TRAN, Kimberly
Priority Data
16/367,70528.03.2019US
Publication Language English (EN)
Filing Language English (EN)
Designated States
Title
(EN) GROUPING STROKES OF DIGITAL INK
(FR) REGROUPEMENT DES TRAITS D'ENCRE NUMÉRIQUE
Abstract
(EN)
Technologies are disclosed for grouping strokes of digital ink. The disclosed technologies receive a new stroke of digital ink and, responsive thereto, identify groups of strokes that are candidates for receiving the new stroke. Heuristics are computed for one of the candidate groups and for the new stroke. A confidence value is computed for the new stroke based upon the heuristics for the new stroke and the candidate group. If the confidence value exceeds a confidence threshold, which can be user-adjustable, the new stroke of digital ink is added to the candidate group. This process can then be repeated for other candidate groups until a group is found for the new stroke. If no group is found, a new group can be created for the new stroke. A machine learning model can also generate weights for use in computing confidence values.
(FR)
L'invention porte sur des technologies de regroupement de traits d'encre numérique. Les technologies selon la présente invention reçoivent un nouveau trait d'encre numérique et, en réponse à celui-ci, identifient des groupes de traits qui sont candidats pour recevoir le nouveau trait. Les heuristiques sont calculées pour l'un des groupes candidats et pour le nouvel AVC. Une valeur de confiance est calculée pour la nouvelle attaque, sur la base des heuristiques de la nouvelle attaque et du groupe candidat. Si la valeur de confiance dépasse un seuil de confiance, qui peut être réglable par l'utilisateur, le nouveau trait d'encre numérique est ajouté au groupe candidat. Ce processus peut ensuite être répété pour d'autres groupes de candidats jusqu'à ce qu'un groupe soit trouvé pour le nouveau trait. Si aucun groupe n'est trouvé, un nouveau groupe peut être créé pour le nouveau trait. Un modèle d'apprentissage machine peut également générer des pondérations à utiliser dans le calcul des valeurs de confiance.
Also published as
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