prikaz prve stranice dokumenta Prepoznavanje gesti ruku
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undergraduate thesis
Prepoznavanje gesti ruku
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. urn:nbn:hr:168:766208
Vrljić, Bjanka
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Vrljić, B. (2022). Prepoznavanje gesti ruku (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:766208

Vrljić, Bjanka. "Prepoznavanje gesti ruku." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:766208

Vrljić, Bjanka. "Prepoznavanje gesti ruku." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:766208

Vrljić, B. (2022). 'Prepoznavanje gesti ruku', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 13 January 2025, https://urn.nsk.hr/urn:nbn:hr:168:766208

Vrljić B. Prepoznavanje gesti ruku [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2022 [cited 2025 January 13] Available at: https://urn.nsk.hr/urn:nbn:hr:168:766208

B. Vrljić, "Prepoznavanje gesti ruku", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:168:766208

Metadata
TitlePrepoznavanje gesti ruku
Title (english)Hand gesture recognition
AuthorBjanka Vrljić
MentorIvica Botički (mentor)
Committee memberIvica Botički (predsjednik povjerenstva)
Committee memberMirjana Domazet-Lošo (član povjerenstva)
Committee memberJuraj Dončević (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2022-07-08, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Završni rad obuhvaća izradu sustava za prepoznavanje slova abecede američkog znakovnog jezika u stvarnom vremenu, što uključuje detekciju ruke na kameri te izradu i korištenje klasifikatora gesti. Detekcija ruke je implementirana pomoću biblioteke MediaPipe. MediaPipe crta pojednostavljeni kostur ruke na ekranu i detektira ključne točke ruke. Te ključne točke se onda prosljeđuju klasifikatoru gesti kako bi napravio predikciju. Klasifikator gesti je ostvaren kao model umjetne neuronske mreže, izrađen pomoću biblioteke TensorFlow. Za treniranje i testiranje modela korišteni su postojeći skupovi podataka s Kaggle. Prikazana je programska implementacija u Pythonu i dobiveni rezultati.
Abstract (english)
This paper covers the development of a system for recognizing the letters of the American Sign Language alphabet in real time, which includes the detection of the hand on the camera and the making of and use of a gesture classifier. Hand detection is implemented using the MediaPipe library. MediaPipe draws a simplified skeleton of the hand on the screen and detects hand key points. These key points are then passed to the gesture classifier in order to make a prediction. The gesture classifier was realized as a model of an artificial neural network, created using the TensorFlow library. Existing Kaggle datasets were used to train and test the model. This paper shows the implementation of this system in Python and the obtained results.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:766208
Study programmeTitle: Computing
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2023-01-15 11:26:09