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Prepoznava tekačev na slikah
ID GRGIČ JELEN, MIHA (Author), ID Batagelj, Borut (Mentor) More about this mentor... This link opens in a new window

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MD5: 2040FDE1B773370A06664743A32EA8AD
PID: 20.500.12556/rul/45f01d40-c588-4bd8-996a-b760f4c2d06a

Abstract
V diplomski nalogi smo razvili rešitev za identifikacijo tekačev na fotografijah športnih prireditev. Za dosego tega cilja, smo izdelali postopek, ki na fotografiji najprej izolira posamezne osebe, nato za vsako osebo izračuna tarčno regijo v kateri se najverjetneje nahaja štartna številka. V naslednjem koraku izvede segmentacijo tarčne regije in izolira posamezne števke. Nato vsak izsek, ki je potencialno števka poskušamo prepoznati z optičnem branjem znakov z uporabo orodja TesseractOCR. Na koncu prepoznane števke dodatno filtriramo in združimo v štartno številko. Predstavljena so vsa uporabljena orodja ter teorija in principi kako sploh delujejo. Nekoliko bolj podrobno smo se posvetili samim detektorjem objektov, saj je ta del ključen za uspešnost celotnega postopka. Opisan je tudi razvit uporabniški vmesnik, ki nam močno olajša pregledovanje fotografij in vizualizacijo rezultatov. Na koncu pregledamo nerešene probleme ter nekaj idej za nadaljni razvoj.

Language:Slovenian
Keywords:detektor objektov, detektor oseb, prepoznava številk, optična prepoznava znakov, nevronske mreže, OpenCV, selektivno iskanje
Work type:Bachelor thesis/paper
Organization:FRI - Faculty of Computer and Information Science
Year:2017
PID:20.500.12556/RUL-96665 This link opens in a new window
Publication date in RUL:09.10.2017
Views:1497
Downloads:552
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Secondary language

Language:English
Title:Runner’s identification from the photos
Abstract:
In the thessis we have developed a solution for identifying runners from photos taken during sport events. For reaching that goal, we developed a procedure, which first isolates each person on the photo. Then we define a target region (for each person), where we belive that the number on the jersey is located. In the next step we execute further image segmentation in order to isolate single digits. After that we use optical character recognition (TesseractOCR) on each of the isolated digit candidates, to determine if it's a number. In the last steps, we perform further result filtering to remove false positive results. The rest of them is joined into the final number. All the tools we have used and the principles behind them, are presented in the paper. We were focusing on object detectors, since this is the key-point in the whole procedure. We also described the user interface we have created for navigation and result visualisation. In the end we explain problems we were not able to solve and ideas for further development.

Keywords:object detector, person detector, number detection, optical character recognition, neuron networks, OpenCV, selective search

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