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1. WO2022072191 - EYEWEAR DISTORTION CORRECTION

Publication Number WO/2022/072191
Publication Date 07.04.2022
International Application No. PCT/US2021/051454
International Filing Date 22.09.2021
IPC
G06T 5/00 2006.1
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
5Image enhancement or restoration
G06T 11/40 2006.1
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
112D image generation
40Filling a planar surface by adding surface attributes, e.g. colour or texture
G06T 3/00 2006.1
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
3Geometric image transformation in the plane of the image
G06T 3/40 2006.1
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
3Geometric image transformation in the plane of the image
40Scaling of a whole image or part thereof
H04N 1/62 2006.1
HELECTRICITY
04ELECTRIC COMMUNICATION TECHNIQUE
NPICTORIAL COMMUNICATION, e.g. TELEVISION
1Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
46Colour picture communication systems
56Processing of colour picture signals
60Colour correction or control
62Retouching, i.e. modification of isolated colours only or in isolated picture areas only
CPC
G06K 9/00
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
G06T 11/00
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
112D [Two Dimensional] image generation
G06T 11/40
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
112D [Two Dimensional] image generation
40Filling a planar surface by adding surface attributes, e.g. colour or texture
G06T 2207/10004
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
2207Indexing scheme for image analysis or image enhancement
10Image acquisition modality
10004Still image; Photographic image
G06T 2207/10016
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
2207Indexing scheme for image analysis or image enhancement
10Image acquisition modality
10016Video; Image sequence
G06T 2207/20081
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
2207Indexing scheme for image analysis or image enhancement
20Special algorithmic details
20081Training; Learning
Applicants
  • SNAP INC. [US]/[US]
Inventors
  • ZAK, Eyal
  • MELAMED, Guy
Agents
  • WEED, Stephen, J.
Priority Data
17/039,33430.09.2020US
Publication Language English (en)
Filing Language English (EN)
Designated States
Title
(EN) EYEWEAR DISTORTION CORRECTION
(FR) CORRECTION DE DISTORSION DE LUNETTES
Abstract
(EN) Systems, methods, and non-transitory computer readable mediums including processes to correct for distortion in images introduced by eyewear (i.e., where the facial region surrounding the eye has a boundary that doesn't match the boundary of an uncovered facial region). The correction includes segmenting images to detect eyewear covered facial regions and facial regions not covered by the eyewear and altering the covered facial regions to match the covered facial boundary to the uncovered facial boundary. Alterations include processing using a machine learning model, applying anti -refraction algorithms, scaling the covered facial region to match boundaries of the uncovered facial region, or a combination thereof.
(FR) L'invention concerne des systèmes, des procédés, et des supports lisibles par ordinateur non transitoires comprenant des processus pour corriger une distorsion dans des images introduites par des lunettes (c'est-à-dire, où la zone du visage qui entoure l’œil a une limite qui ne correspond pas à la limite d'une zone du visage non recouverte). La correction comprend la segmentation d'images pour détecter des zones de visage recouvertes par des lunettes et des zones de visage non recouvertes par les lunettes et la modification des zones de visage recouvertes pour correspondre à la limite du visage recouverte par rapport à la limite du visage non recouverte. Des modifications comprennent le traitement à l'aide d'un modèle d'apprentissage machine, l'application d'algorithmes anti-réfraction, la mise à l'échelle de la zone de visage recouverte pour correspondre aux limites de la zone de visage non recouverte, ou une combinaison de ceux-ci.
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