G06V 10/77 Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
Introduced: January 2022
Full Title
Full titles differ between systems:
Arrangements for image or video recognition or understanding > using pattern recognition or machine learning > Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
Arrangements for image or video recognition or understanding (character recognition in images or video G06V30/10) > using pattern recognition or machine learning (optical pattern recognition or electronic computations therefor G06V10/88) > Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
Additional Content IPC
BSS blind source separation eigenface eigenfaces name given to a set of eigenvectors obtained by principal component analysis when used in face recognition. ICA independent component analysis LDA linear discriminant analysis MDS multidimensional scaling PCA principal component analysis SOM self-organising map
Of 7 combined children, 6 exist in both systems.
1 codes are CPC-only extensions.
1 shared codes have differing titles between IPC and CPC.
IPC defines codes here since 2022.
Child Classifications
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- G06V 10/771 Feature selection, e.g. selecting representative features from a multi-dimensional feature space since 2022 IPC+CPC Available in IPC and CPC
- G06V 10/772 Determining representative reference patterns, e.g. averaging or distorting patterns; Generating dictionaries since 2022 IPC+CPC Available in IPC and CPC
- G06V 10/774 Generating sets of training patterns; Bootstrap methods, e.g. bagging or boosting since 2022 +2 CPC IPC+CPC Available in IPC and CPC
- G06V 10/778 Active pattern-learning, e.g. online learning of image or video features since 2022 +2 CPC IPC+CPC Available in IPC and CPC
- G06V 10/80 Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level (multimodal speaker identification or verification G10L17/10) since 2022 +5 CPC IPC+CPC Available in IPC and CPC
Top Applicants
Top Applicants (IPC)
Class G06,2013–2023, worldwide · Source: EPO PATSTAT
- SAMSUNG ELECTRONICS COMPANY KR 66,669
- IBM (INTERNATIONAL BUSINESS MACHINES CORPORATION) US 62,313
- MICROSOFT TECHNOLOGY LICENSING US 41,918
- GOOGLE US 32,969
- SGCC(STATE GRID CORPORATION OF CHINA) 30,822
- INTEL CORPORATION US 30,010
- TENCENT TECHNOLOGY (SHENZHEN) COMPANY 28,235
- HUAWEI TECHNOLOGIES COMPANY CN 26,079
- APPLE US 21,891
- HUAWEI TECHNOLOGIES COMPANY 20,505
Top Applicants (CPC)
Class G06,2013–2023, worldwide · Source: EPO PATSTAT
- SAMSUNG ELECTRONICS COMPANY KR 76,952
- IBM (INTERNATIONAL BUSINESS MACHINES CORPORATION) US 62,841
- MICROSOFT TECHNOLOGY LICENSING US 44,778
- GOOGLE US 35,735
- INTEL CORPORATION US 32,087
- HUAWEI TECHNOLOGIES COMPANY CN 30,572
- TENCENT TECHNOLOGY (SHENZHEN) COMPANY 25,023
- APPLE US 23,482
- SGCC(STATE GRID CORPORATION OF CHINA) 22,548
- HUAWEI TECHNOLOGIES COMPANY 20,917