WIPO logo
Mobile | Deutsch | Español | Français | 日本語 | 한국어 | Português | Русский | 中文 | العربية |
PATENTSCOPE

Search International and National Patent Collections
World Intellectual Property Organization
Search
 
Browse
 
Translate
 
Options
 
News
 
Login
 
Help
 
Machine translation
1. (WO2013048159) METHOD, APPARATUS AND COMPUTER READABLE RECORDING MEDIUM FOR DETECTING A LOCATION OF A FACE FEATURE POINT USING AN ADABOOST LEARNING ALGORITHM
Latest bibliographic data on file with the International Bureau   

Pub. No.:    WO/2013/048159    International Application No.:    PCT/KR2012/007843
Publication Date: 04.04.2013 International Filing Date: 27.09.2012
IPC:
G06K 9/46 (2006.01)
Applicants: INTEL CORPORATION [KR/KR]; 2200 Mission College Blvd. Santa Clara, CA 95054 (KR)
Inventors: CHEON, Yeong Jae; (KR).
PARK, Yong Chan; (KR)
Agent: CHANG, Soo Kil; Kim & Chang, Seyang B/D 39 Sajikro 8-gil Jongno-gu Seoul 110-720 (KR)
Priority Data:
10-2011-0097794 27.09.2011 KR
Title (EN) METHOD, APPARATUS AND COMPUTER READABLE RECORDING MEDIUM FOR DETECTING A LOCATION OF A FACE FEATURE POINT USING AN ADABOOST LEARNING ALGORITHM
(FR) PROCÉDÉ, APPAREIL ET SUPPORT D'ENREGISTREMENT LISIBLE PAR ORDINATEUR POUR DÉTECTER UN EMPLACEMENT D'UN POINT DE CARACTÉRISTIQUE DE VISAGE À L'AIDE D'UN ALGORITHME D'APPRENTISSAGE ADABOOST
(KO) 아다부스트 학습 알고리즘을 이용하여 얼굴 특징점 위치를 검출하기 위한 방법, 장치, 및 컴퓨터 판독 가능한 기록 매체
Abstract: front page image
(EN)The present invention relates to a method, an apparatus and a computer readable recording medium for detecting the location of face feature point using an Adaboost learning algorithm. According to one embodiment of the present invention, a method for detecting a location of a face feature point comprises: (a) a step of classifying a sub-window image into a first recommended feature point candidate image and a first non-recommended feature point candidate image using first feature patterns selected by an Adaboost learning algorithm, and generating first feature point candidate location information on the first recommended feature point candidate image; and (b) a step of re-classifying said sub-window image classified into said first non-recommended feature point candidate image, into a second recommended feature point candidate image and a second non-recommended feature point candidate image using second feature patterns selected by the Adaboost learning algorithm, and generating second feature point candidate location information on the second recommended feature point recommended candidate image.
(FR)La présente invention concerne un procédé, un appareil et un support d'enregistrement lisible par ordinateur pour détecter l'emplacement d'un point de caractéristique de visage à l'aide d'un algorithme d'apprentissage Adaboost. Selon un mode de réalisation de la présente invention, un procédé de détection d'un emplacement d'un point de caractéristique de visage comprend : (a) une étape consistant à classer une image de sous-fenêtre en une première image de point de caractéristique candidat recommandé et en une première image de point de caractéristique candidat non recommandé à l'aide de premiers motifs de caractéristique sélectionnés par un algorithme d'apprentissage Adaboost, et à générer des premières informations d'emplacement de point de caractéristique candidat sur la première image de point de caractéristique candidat recommandé ; et (b) une étape consistant à reclasser ladite image de sous-fenêtre classée en ladite première image de point de caractéristique candidat non recommandé, en une seconde image de point de caractéristique candidat recommandé et en une seconde image de point de caractéristique candidat non recommandé à l'aide de seconds motifs de caractéristique sélectionnés par l'algorithme d'apprentissage Adaboost, et à générer des secondes informations d'emplacement de point de caractéristique candidat sur la seconde image de point de caractéristique candidat recommandé.
(KO)본 발명은 아다부스트 학습 알고리즘을 이용한 얼굴 특징점 위치를 검출하기 위한 방법, 장치, 및 컴퓨터 판독 가능한 기록 매체에 관한 것이다. 본 발명의 일 태양에 따르면, 얼굴 특징점 위치를 검출하기 위한 방법으로서, (a) 아다부스트 학습 알고리즘에 의해서 선택된 제1특징 패턴들을 이용하여 서브 윈도우 이미지를 제1특징점 후보 추천 이미지와 제1특징점 후보 비추천 이미지로 분류하고, 상기 제1특징점 후보 추천 이미지의 제1특징점 후보 위치 정보를 발생하는 단계, 및 (b) 상기 아다부스트 학습 알고리즘에 의해서 선택된 제2특징 패턴들을 이용하여 상기 제1특징점 후보 비추천 이미지로 분류된 상기 서브 윈도우 이미지를 제2특징점 후보 추천 이미지와 제2특징점 후보 비추천 이미지로 재분류하고, 상기 제2특징점 후보 추천 이미지의 제2특징점 후보 위치 정보를 발생하는 단계를 포함하는 방법이 제공된다.
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, 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: Korean (KO)
Filing Language: Korean (KO)