SG11201811330WA - Detecting objects in video data - Google Patents

Detecting objects in video data

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Publication number
SG11201811330WA
SG11201811330WA SG11201811330WA SG11201811330WA SG11201811330WA SG 11201811330W A SG11201811330W A SG 11201811330WA SG 11201811330W A SG11201811330W A SG 11201811330WA SG 11201811330W A SG11201811330W A SG 11201811330WA SG 11201811330W A SG11201811330W A SG 11201811330WA
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SG
Singapore
Prior art keywords
london
international
representation
video data
pct
Prior art date
Application number
SG11201811330WA
Inventor
John Brendan Mccormac
Ankur Handa
Andrew Davison
Stefan Leutenegger
Original Assignee
Imperial College Of Science Technology And Medicine
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Publication date
Application filed by Imperial College Of Science Technology And Medicine filed Critical Imperial College Of Science Technology And Medicine
Publication of SG11201811330WA publication Critical patent/SG11201811330WA/en

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Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/40—Scenes; Scene-specific elements in video content
    • G06V20/41—Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/60—Type of objects
    • G06V20/64—Three-dimensional objects
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/213—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
    • G06F18/2148—Generating training patterns; Bootstrap methods, e.g. bagging or boosting characterised by the process organisation or structure, e.g. boosting cascade
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
    • G06F18/2415—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on parametric or probabilistic models, e.g. based on likelihood ratio or false acceptance rate versus a false rejection rate
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/20—Image preprocessing
    • G06V10/28—Quantising the image, e.g. histogram thresholding for discrimination between background and foreground patterns
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/77—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
    • G06V10/7715—Feature extraction, e.g. by transforming the feature space, e.g. multi-dimensional scaling [MDS]; Mappings, e.g. subspace methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/60—Type of objects
    • G06V20/64—Three-dimensional objects
    • G06V20/647—Three-dimensional objects by matching two-dimensional images to three-dimensional objects
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N13/00—Stereoscopic video systems; Multi-view video systems; Details thereof
    • H04N13/10—Processing, recording or transmission of stereoscopic or multi-view image signals
    • H04N13/106—Processing image signals
    • H04N13/172—Processing image signals image signals comprising non-image signal components, e.g. headers or format information
    • H04N13/183—On-screen display [OSD] information, e.g. subtitles or menus

Abstract

INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization 11111111111111111111111111111111111111111111111111H11111111111111111111111111110111111 International Bureau (10) International Publication Number (43) International Publication Date .....0\"\" WO 2017/220966 Al 28 December 2017 (28.12.2017) WIP0 I PCT (51) International Patent Classification: G06K 9/00 (2006.01) GOOF 17/00 (2006.01) (21) International Application Number: (22) International Filing Date: (25) Filing Language: (26) Publication Language: (30) Priority Data: 1611033.0 24 June 2016 (24.06.2016) (71) Applicant: IMPERIAL COLLEGE TECHNOLOGY AND MEDICINE Road, London Greater London SW7 2AZ (GB). (72) Inventors: MCCORMAC, bridge Down BT32 3TA (GB). ters Court, Porchester Road, London Greater London W2 5DS (GB). DAVISON, Andrew; Department of Comput- GOOK 9/62 (2006.01) ing, Huxley Building, 180 Queens Gate, London Greater London SW7 2RH (GB). LEUTENEGGER, Stefan; 54 Shorrolds Road, London Greater London SW6 7TP (GB). PCT/GB2017/051679 (74) Agent: EIP; Fairfax House, 15 Fulwood Place, London Greater London WC1V 6HU (GB). 09 June 2017 (09.06.2017) (81) Designated States (unless otherwise indicated, for every English kind of national protection available): AE, AG, AL, AM, AO, AT, AU, AZ, BA, BB, BG, BH, BN, BR, BW, BY, BZ, English 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, GB KR, KW, KZ, LA, LC, LK, LR, LS, LU, LY, MA, MD, ME, OF SCIENCE, MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, [GB/GB]; Exhibition 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. John; 5 Killaney Lane, Ban- HANDA, Ankur; 103 Pe- (84) Designated States (unless otherwise indicated, for every kind of regional protection available): ARIPO (BW, GH, IN VIDEO DATA 605 610 , 615 Fig. 6 of a three-dimensional (3D) space to be or 'surfer representation, where the geometry ordinate system. -label probability values image classifier. Surface elements that element representation using an estimated (615) based on the object-label probability element representation of objects present better use of the 3D representation. (54) Title: DETECTING OBJECTS 600 Determine object-label probabilities for 2D frames Identify surfels in 3D representation V Update surfel object-label probabilities -labelled representations is a surface element within a 3D co- using a two-dimensional a projection of the surface are then updated -labelled 3D surface applications to make herein enable semantically examples, a 3D representation of surfaces that are defined data may be determined (605) are identified (610) based on values for the surface elements This results in a semantically computer vision and/or robotic -2 0 (57) : Certain examples described ---(+ generated from video data. In described of the space is modelled using a plurality c l for spatial elements of frames of video © correspond to the spatial elements N pose for a frame. -label probability --.... values for corresponding spatial elements. I N in the video data. This data enables 1-1 0 ei O [Continued on next page] WO 2017/220966 Al 0111 GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, ST, SZ, TZ, UG, ZM, ZW), Eurasian (AM, AZ, BY, KG, KZ, RU, TJ, TM), European (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), OAPI (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW, KM, ML, MR, NE, SN, TD, TG). Published: — with international search report (Art. 21(3))
SG11201811330WA 2016-06-24 2017-06-09 Detecting objects in video data SG11201811330WA (en)

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Application Number Priority Date Filing Date Title
GB1611033.0A GB2554633B (en) 2016-06-24 2016-06-24 Detecting objects in video data
PCT/GB2017/051679 WO2017220966A1 (en) 2016-06-24 2017-06-09 Detecting objects in video data

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SG11201811330WA true SG11201811330WA (en) 2019-01-30

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US (1) US10915731B2 (en)
EP (1) EP3475875A1 (en)
JP (1) JP7009399B2 (en)
KR (1) KR20190038808A (en)
CN (1) CN109643368B (en)
AU (1) AU2017281822A1 (en)
BR (1) BR112018076556A2 (en)
GB (1) GB2554633B (en)
RU (1) RU2019101759A (en)
SG (1) SG11201811330WA (en)
WO (1) WO2017220966A1 (en)

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RU2019101759A3 (en) 2020-09-30
EP3475875A1 (en) 2019-05-01
AU2017281822A1 (en) 2019-01-03
GB2554633A (en) 2018-04-11
US10915731B2 (en) 2021-02-09
RU2019101759A (en) 2020-07-24
US20190147220A1 (en) 2019-05-16
WO2017220966A1 (en) 2017-12-28
JP2019520654A (en) 2019-07-18
CN109643368A (en) 2019-04-16
JP7009399B2 (en) 2022-01-25
GB201611033D0 (en) 2016-08-10
CN109643368B (en) 2023-09-22
BR112018076556A2 (en) 2019-04-02
KR20190038808A (en) 2019-04-09
GB2554633B (en) 2020-01-22

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