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1. (WO2013160192) METHOD FOR BINARY CLASSIFICATION OF A QUERY IMAGE
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Pub. No.:
WO/2013/160192
International Application No.:
PCT/EP2013/058108
Publication Date:
31.10.2013
International Filing Date:
18.04.2013
IPC:
G06F 17/30
(2006.01)
G
PHYSICS
06
COMPUTING; CALCULATING; COUNTING
F
ELECTRIC DIGITAL DATA PROCESSING
17
Digital computing or data processing equipment or methods, specially adapted for specific functions
30
Information retrieval; Database structures therefor
Applicants:
ATG ADVANCED SWISS TECHNOLOGY GROUP AG
[CH/CH]; Bahnhofstrasse 3 CH-8808 Pfäffikon (CH)
Inventors:
LIENHART, Rainer
; (DE).
RIES, Christian
; (DE)
Agent:
LIEDTKE, Markus
; Liedtke & Partner Patentanwälte Gerhart-Hauptmann-Straße 10/11 99096 Erfurt (DE)
Priority Data:
12165880.1
27.04.2012
EP
Title
(EN)
METHOD FOR BINARY CLASSIFICATION OF A QUERY IMAGE
(FR)
PROCÉDÉ DE CLASSIFICATION BINAIRE D'UNE IMAGE REQUÊTE
Abstract:
(EN)
The invention relates to a method for the training of a classifier based on weakly labeled images and for the binary classification of an image. The training of the classifier comprises the steps of automatically and iteratively determining initial regions of interest for a training set and further on refining said regions of interest and adapting the classifier onto the refined regions of interest by a classifier refinement procedure. Further on, for a query image with unknown classification, an initial region of interest is determined and refined as to maximize the probability value derived at the output of said classifier. The query image is automatically assigned a negative classification label if said probability value is lower than or equal to a predetermined first threshold. The query image is automatically assigned a positive classification label if said probability value is greater than a predetermined second threshold.
(FR)
L'invention concerne un procédé pour l'apprentissage d'un classificateur sur la base d'images faiblement marquées et pour la classification binaire d'une image. L'apprentissage du classificateur comprend les étapes consistant à déterminer de façon automatique et itérative des régions d'intérêt initiales pour un ensemble d'apprentissage puis à affiner lesdites régions d'intérêt et à adapter le classificateur sur les régions d'intérêt affinées par une procédure d'affinage de classificateur. L'apprentissage consiste ensuite, pour une image requête de classification inconnue, à déterminer et à affiner une région d'intérêt initiale dans le but de maximiser la valeur de probabilité obtenue à la sortie dudit classificateur. L'image requête se voit affecter automatiquement une marque de classification négative si ladite valeur de probabilité est inférieure ou égale à un premier seuil prédéfini. L'image requête se voit affecter automatiquement une marque de classification positive si ladite valeur de probabilité est supérieure à un deuxième seuil prédéfini.
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, DK, DM, DO, DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, HR, HU, ID, IL, IN, IS, JP, KE, KG, KM, KN, KP, KR, KZ, LA, LC, LK, LR, LS, LT, 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, 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 (BW, GH, GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, SZ, TZ, UG, ZM, ZW)
Eurasian Patent Organization (AM, AZ, BY, KG, KZ, RU, TJ, TM)
European Patent Office (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, ML, MR, NE, SN, TD, TG).
Publication Language:
English (
EN
)
Filing Language:
English (
EN
)