Patent SG-11201811330W-A (SG)
Title: Detecting objects in video data
Inventor: MCCORMAC JOHN BRENDAN
IPC: G06F17/00
Filed: 2017-06-09
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))