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1. (WO2019045982) VIEWPOINT INVARIANT OBJECT RECOGNITION BY SYNTHESIZATION AND DOMAIN ADAPTATION
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Pub. No.: WO/2019/045982 International Application No.: PCT/US2018/045911
Publication Date: 07.03.2019 International Filing Date: 09.08.2018
IPC:
G06K 9/20 (2006.01) ,G06K 9/46 (2006.01) ,G06K 9/62 (2006.01) ,G06N 3/08 (2006.01)
G PHYSICS
06
COMPUTING; CALCULATING; COUNTING
K
RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
9
Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
20
Image acquisition
G PHYSICS
06
COMPUTING; CALCULATING; COUNTING
K
RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
9
Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
36
Image preprocessing, i.e. processing the image information without deciding about the identity of the image
46
Extraction of features or characteristics of the image
G PHYSICS
06
COMPUTING; CALCULATING; COUNTING
K
RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
9
Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
62
Methods or arrangements for recognition using electronic means
G PHYSICS
06
COMPUTING; CALCULATING; COUNTING
N
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3
Computer systems based on biological models
02
using neural network models
08
Learning methods
Applicants:
NEC LABORATORIES AMERICA, INC. [US/US]; 4 Independence Way Suite 200 Princeton, New Jersey 08540, US
Inventors:
SOHN, Kihyuk; US
TRAN, Luan; US
YU, Xiang; US
CHANDRAKER, Manmohan; US
Agent:
KOLODKA, Joseph; US
Priority Data:
16/051,92401.08.2018US
16/051,98001.08.2018US
62/553,09031.08.2017US
62/585,75814.11.2017US
Title (EN) VIEWPOINT INVARIANT OBJECT RECOGNITION BY SYNTHESIZATION AND DOMAIN ADAPTATION
(FR) RECONNAISSANCE D'OBJET D'INVARIANT DE POINT DE VUE PAR SYNTHÈSE ET ADAPTATION DE DOMAINE
Abstract:
(EN) Systems and methods for performing domain adaptation include collecting a labeled source image having a view of an object. Viewpoints of the object in the source image are synthesized to generate view augmented source images. Photometrics of each of the viewpoints of the object are adjusted to generate lighting and view augmented source images. Features are extracted from each of the lighting and view augmented source images with a first feature extractor and from captured images captured by an image capture device with a second feature extractor. The extracted features are classified using domain adaptation with domain adversarial learning between extracted features of the captured images and extracted features of the lighting and view augmented source images. Labeled target images are displayed corresponding to each of the captured images including labels corresponding to classifications of the extracted features of the captured images.
(FR) L'invention concerne des systèmes et des procédés permettant d'effectuer une adaptation de domaine, lesdits procédés consistant à collecter une image source étiquetée comprenant une vue d'un objet. Des points de vue de l'objet dans l'image source sont synthétisés pour générer des images source augmentées de visualisation. Les photométriques de chacun des points de vue de l'objet sont ajustées pour générer des images source augmentées d'éclairage et de visualisation. Des caractéristiques sont extraites à partir de chacune des images sources augmentées d'éclairage et de visualisation à l'aide d'un premier extracteur de caractéristiques et à partir des images capturées par un dispositif de capture d'images à l'aide d'un second extracteur de caractéristiques. Les caractéristiques extraites sont classées à l'aide d'une adaptation de domaine avec un apprentissage contradictoire de domaine entre les caractéristiques extraites des images capturées et les caractéristiques extraites des images de source augmentées d'éclairage et de visualisation. Les images cibles étiquetées affichées correspondent à chacune des images capturées comprenant des étiquettes correspondant à des classifications des caractéristiques extraites des images capturées.
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Designated States: AE, AG, AL, AM, AO, AT, AU, AZ, BA, BB, BG, BH, BN, BR, BW, BY, BZ, CA, CH, CL, CN, CO, CR, CU, CZ, DE, DJ, DK, DM, DO, DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, HR, HU, ID, IL, IN, IR, IS, JO, JP, KE, KG, KH, KN, KP, KR, KW, KZ, LA, LC, LK, LR, LS, LU, LY, MA, MD, ME, MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, SC, SD, SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW
African Regional Intellectual Property Organization (ARIPO) (BW, GH, GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, ST, SZ, TZ, UG, ZM, ZW)
Eurasian Patent Office (AM, AZ, BY, KG, KZ, RU, TJ, TM)
European Patent Office (EPO) (AL, AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HR, HU, IE, IS, IT, LT, LU, LV, MC, MK, MT, NL, NO, PL, PT, RO, RS, SE, SI, SK, SM, TR)
African Intellectual Property Organization (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW, KM, ML, MR, NE, SN, TD, TG)
Publication Language: English (EN)
Filing Language: English (EN)