G | PHYSICS | |||
Note(s)
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G06 | COMPUTING; CALCULATING OR COUNTING | |||
Note(s) [2011.01]
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G06V | IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING [2022.01] | |||
Note(s) [2022.01]
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G06V 10/00 | Arrangements for image or video recognition or understanding (character recognition in images or video G06V 30/10) [2022.01] | |||
G06V 10/10 | • Image acquisition (document image scanning and transmission H04N 1/00; control of digital cameras H04N 23/60) [2022.01] | |||
G06V 10/12 | • • Details of acquisition arrangements; Constructional details thereof [2022.01] | |||
G06V 10/14 | • • • Optical characteristics of the device performing the acquisition or on the illumination arrangements [2022.01] | |||
G06V 10/141 | • • • • Control of illumination [2022.01] | |||
G06V 10/143 | • • • • Sensing or illuminating at different wavelengths [2022.01] | |||
G06V 10/145 | • • • • Illumination specially adapted for pattern recognition, e.g. using gratings [2022.01] | |||
G06V 10/147 | • • • • Details of sensors, e.g. sensor lenses (fingerprint or palmprint sensors G06V 40/13; vascular sensors G06V 40/145; eye sensors G06V 40/19) [2022.01] | |||
G06V 10/20 | • Image preprocessing [2022.01] | |||
G06V 10/22 | • • by selection of a specific region containing or referencing a pattern; Locating or processing of specific regions to guide the detection or recognition [2022.01] | |||
G06V 10/24 | • • Aligning, centring, orientation detection or correction of the image [2022.01] | |||
G06V 10/25 | • • | |||
G06V 10/26 | • • Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion [2022.01] | |||
G06V 10/28 | • • Quantising the image, e.g. histogram thresholding for discrimination between background and foreground patterns [2022.01] | |||
G06V 10/30 | • • Noise filtering [2022.01] | |||
G06V 10/32 | • • Normalisation of the pattern dimensions [2022.01] | |||
G06V 10/34 | • • Smoothing or thinning of the pattern; Morphological operations; Skeletonisation [2022.01] | |||
G06V 10/36 | • • Applying a local operator, i.e. means to operate on image points situated in the vicinity of a given point; Non-linear local filtering operations, e.g. median filtering [2022.01] | |||
G06V 10/40 | • Extraction of image or video features [2022.01] | |||
G06V 10/42 | • • Global feature extraction by analysis of the whole pattern, e.g. using frequency domain transformations or autocorrelation [2022.01] | |||
G06V 10/422 | • • • for representing the structure of the pattern or shape of an object therefor [2022.01] | |||
G06V 10/424 | • • • • Syntactic representation, e.g. by using alphabets or grammars [2022.01] | |||
G06V 10/426 | • • • • Graphical representations [2022.01] | |||
G06V 10/44 | • • Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components [2022.01] | |||
G06V 10/46 | • • Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]; Salient regional features (colour feature extraction G06V 10/56) [2022.01] | |||
G06V 10/48 | • • by mapping characteristic values of the pattern into a parameter space, e.g. Hough transformation [2022.01] | |||
G06V 10/50 | • • | |||
G06V 10/52 | • • Scale-space analysis, e.g. wavelet analysis (multi-scale boundary representations G06V 10/42) [2022.01] | |||
G06V 10/54 | • • relating to texture [2022.01] | |||
G06V 10/56 | • • relating to colour [2022.01] | |||
G06V 10/58 | • • relating to hyperspectral data [2022.01] | |||
G06V 10/60 | • • relating to illumination properties, e.g. using a reflectance or lighting model [2022.01] | |||
G06V 10/62 | • • relating to a temporal dimension, e.g. time-based feature extraction; Pattern tracking [2022.01] | |||
G06V 10/70 | • using pattern recognition or machine learning (optical pattern recognition or electronic computations therefor G06V 10/88) [2022.01] | |||
G06V 10/72 | • • Data preparation, e.g. statistical preprocessing of image or video features [2022.01] | |||
G06V 10/74 | • • | |||
G06V 10/75 | • • • | |||
G06V 10/762 | • • using clustering, e.g. of similar faces in social networks [2022.01] | |||
G06V 10/764 | • • using classification, e.g. of video objects [2022.01] | |||
G06V 10/766 | • • using regression, e.g. by projecting features on hyperplanes [2022.01] | |||
G06V 10/77 | • • | |||
G06V 10/771 | • • • | |||
G06V 10/772 | • • • | |||
G06V 10/774 | • • • Generating sets of training patterns; Bootstrap methods, e.g. bagging or boosting [2022.01] | |||
G06V 10/776 | • • • Validation; Performance evaluation [2022.01] | |||
G06V 10/778 | • • • | |||
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 G10L 17/10) [2022.01] | |||
G06V 10/82 | • • using neural networks [2022.01] | |||
G06V 10/84 | • • using probabilistic graphical models from image or video features, e.g. Markov models or Bayesian networks [2022.01] | |||
G06V 10/86 | • • using syntactic or structural representations of the image or video pattern, e.g. symbolic string recognition; using graph matching [2022.01] | |||
G06V 10/88 | • Image or video recognition using optical means, e.g. reference filters, holographic masks, frequency domain filters or spatial domain filters [2022.01] | |||
G06V 10/94 | • Hardware or software architectures specially adapted for image or video understanding [2022.01] | |||
G06V 10/96 | • Management of image or video recognition tasks [2022.01] | |||
G06V 10/98 | • | |||
G06V 20/00 | ||||
Note(s) [2022.01]
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G06V 20/05 | • Underwater scenes [2022.01] | |||
G06V 20/10 | • Terrestrial scenes (scenes under surveillance with static cameras G06V 20/52; scenes perceived from the exterior of a vehicle G06V 20/56; scenes perceived from the interior of a vehicle G06V 20/59) [2022.01] | |||
G06V 20/13 | • • Satellite images [2022.01] | |||
G06V 20/17 | • • taken from planes or by drones [2022.01] | |||
G06V 20/20 | • in augmented reality scenes [2022.01] | |||
G06V 20/30 | • in albums, collections or shared content, e.g. social network photos or video [2022.01] | |||
G06V 20/40 | • in video content (extracting overlay text G06V 20/62; video retrieval G06F 16/70; processing of video elementary streams in video servers H04N 21/234; processing of video elementary streams in video clients H04N 21/44) [2022.01] | |||
G06V 20/50 | • Context or environment of the image [2022.01] | |||
G06V 20/52 | • • Surveillance or monitoring of activities, e.g. for recognising suspicious objects (recognising microscopic objects G06V 20/69) [2022.01] | |||
G06V 20/54 | • • • of traffic, e.g. cars on the road, trains or boats [2022.01] | |||
G06V 20/56 | • • exterior to a vehicle by using sensors mounted on the vehicle [2022.01] | |||
G06V 20/58 | • • • Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads [2022.01] | |||
G06V 20/59 | • • inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions [2022.01] | |||
G06V 20/60 | • Type of objects [2022.01] | |||
G06V 20/62 | • • Text, e.g. of license plates, overlay texts or captions on TV images [2022.01] | |||
G06V 20/64 | • • Three-dimensional objects [2022.01] | |||
G06V 20/66 | • • Trinkets, e.g. shirt buttons or jewellery items (recognising microscopic objects G06V 20/69) [2022.01] | |||
G06V 20/68 | • • Food, e.g. fruit or vegetables [2022.01] | |||
G06V 20/69 | • • Microscopic objects, e.g. biological cells or cellular parts [2022.01] | |||
G06V 20/70 | • Labelling scene content, e.g. deriving syntactic or semantic representations [2022.01] | |||
G06V 20/80 | • Recognising image objects characterised by unique random patterns [2022.01] | |||
G06V 20/90 | • Identifying an image sensor based on its output data [2022.01] | |||
G06V 30/00 | ||||
Note(s) [2022.01]
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G06V 30/10 | • Character recognition [2022.01] | |||
G06V 30/12 | • • Detection or correction of errors, e.g. by rescanning the pattern [2022.01] | |||
G06V 30/14 | • • Image acquisition [2022.01] | |||
G06V 30/142 | • • • using hand-held instruments; Constructional details of the instruments [2022.01] | |||
G06V 30/144 | • • • using a slot moved over the image; using discrete sensing elements at predetermined points; using automatic curve following means [2022.01] | |||
G06V 30/146 | • • • Aligning or centering of the image pick-up or image-field [2022.01] | |||
G06V 30/148 | • • • Segmentation of character regions [2022.01] | |||
G06V 30/16 | • • Image preprocessing [2022.01] | |||
G06V 30/162 | • • • Quantising the image signal [2022.01] | |||
G06V 30/164 | • • • Noise filtering [2022.01] | |||
G06V 30/166 | • • • Normalisation of pattern dimensions [2022.01] | |||
G06V 30/168 | • • • Smoothing or thinning of the pattern; Skeletonisation [2022.01] | |||
G06V 30/18 | • • Extraction of features or characteristics of the image [2022.01] | |||
G06V 30/182 | • • • by coding the contour of the pattern [2022.01] | |||
G06V 30/184 | • • • by analysing segments intersecting the pattern [2022.01] | |||
G06V 30/186 | • • • by deriving mathematical or geometrical properties from the whole image [2022.01] | |||
G06V 30/19 | • • Recognition using electronic means [2022.01] | |||
G06V 30/192 | • • • using simultaneous comparisons or correlations of the image signals with a plurality of references [2022.01] | |||
G06V 30/194 | • • • • References adjustable by an adaptive method, e.g. learning [2022.01] | |||
G06V 30/196 | • • • using sequential comparisons of the image signals with a plurality of references [2022.01] | |||
G06V 30/198 | • • • • the selection of the next reference depending on the result of the preceding comparison [2022.01] | |||
G06V 30/199 | • • Arrangements for recognition using optical reference masks, e.g. holographic masks [2022.01] | |||
G06V 30/20 | • • Combination of acquisition, preprocessing or recognition functions [2022.01] | |||
G06V 30/22 | • • characterised by the type of writing [2022.01] | |||
G06V 30/222 | • • • of characters separated by spaces [2022.01] | |||
G06V 30/224 | • • • of printed characters having additional code marks or containing code marks [2022.01] | |||
G06V 30/226 | • • • of cursive writing [2022.01] | |||
G06V 30/228 | • • • of three-dimensional handwriting, e.g. writing in the air [2022.01] | |||
G06V 30/24 | • • characterised by the processing or recognition method (segmentation of character regions G06V 30/148) [2022.01] | |||
G06V 30/242 | • • • Division of the character sequences into groups prior to recognition; Selection of dictionaries [2022.01] | |||
G06V 30/244 | • • • • using graphical properties, e.g. alphabet type or font [2022.01] | |||
G06V 30/246 | • • • • using linguistic properties, e.g. specific for English or German language [2022.01] | |||
G06V 30/26 | • • Techniques for post-processing, e.g. correcting the recognition result [2022.01] | |||
G06V 30/262 | • • • using context analysis, e.g. lexical, syntactic or semantic context [2022.01] | |||
G06V 30/28 | • • specially adapted to the type of the alphabet, e.g. Latin alphabet [2022.01] | |||
G06V 30/30 | • • based on the type of data [2022.01] | |||
G06V 30/302 | • • • Images containing characters for discriminating human versus automated computer access [2022.01] | |||
G06V 30/304 | • • • Music notations [2022.01] | |||
G06V 30/32 | • • Digital ink [2022.01] | |||
G06V 30/40 | • Document-oriented image-based pattern recognition [2022.01] | |||
G06V 30/41 | • • Analysis of document content (recognition of printed characters based on code marks G06V 30/224) [2022.01] | |||
G06V 30/412 | • • • Layout analysis of documents structured with printed lines or input boxes, e.g. business forms or tables [2022.01] | |||
G06V 30/413 | • • • Classification of content, e.g. text, photographs or tables [2022.01] | |||
G06V 30/414 | • • • Extracting the geometrical structure, e.g. layout tree; Block segmentation, e.g. bounding boxes for graphics or text [2022.01] | |||
G06V 30/416 | • • • Extracting the logical structure, e.g. chapters, sections or page numbers; Identifying elements of the document, e.g. authors [2022.01] | |||
G06V 30/418 | • • • Document matching, e.g. of document images [2022.01] | |||
G06V 30/42 | • • based on the type of document [2022.01] | |||
G06V 30/422 | • • • Technical drawings; Geographical maps [2022.01] | |||
G06V 30/424 | • • • Postal images, e.g. labels or addresses on parcels or postal envelopes [2022.01] | |||
G06V 40/00 | Recognition of biometric, human-related or animal-related patterns in image or video data [2022.01] | |||
G06V 40/10 | • Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands [2022.01] | |||
G06V 40/12 | • • Fingerprints or palmprints [2022.01] | |||
G06V 40/13 | • • • Sensors therefor [2022.01] | |||
G06V 40/14 | • • Vascular patterns [2022.01] | |||
G06V 40/145 | • • • Sensors therefor [2022.01] | |||
G06V 40/16 | • • Human faces, e.g. facial parts, sketches or expressions [2022.01] | |||
G06V 40/18 | • • Eye characteristics, e.g. of the iris [2022.01] | |||
G06V 40/19 | • • • Sensors therefor [2022.01] | |||
G06V 40/20 | • Movements or behaviour, e.g. gesture recognition (recognition of facial expressions G06V 40/16) [2022.01] | |||
G06V 40/30 | • Writer recognition; Reading and verifying signatures [2022.01] | |||
G06V 40/40 | • Spoof detection, e.g. liveness detection [2022.01] | |||
G06V 40/50 | • Maintenance of biometric data or enrolment thereof [2022.01] | |||
G06V 40/60 | • Static or dynamic means for assisting the user to position a body part for biometric acquisition [2022.01] | |||
G06V 40/70 | • Multimodal biometrics, e.g. combining information from different biometric modalities [2022.01] |