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Title:
AVTOMATSKO PREPOZNAVANJE UST IZ DIGITALNIH POSNETKOV
Authors:
ID
Leber, Žiga
(Author)
ID
Potočnik, Božidar
(Mentor)
More about this mentor...
Files:
UN_Leber_Ziga_2015.pdf
(2,52 MB)
MD5: 814AA69349A913A98C53CBFD41546EC4
Language:
Slovenian
Work type:
Bachelor thesis/paper
Typology:
2.11 - Undergraduate Thesis
Organization:
FERI - Faculty of Electrical Engineering and Computer Science
Abstract:
Diplomsko delo se osredotoča na avtomatsko prepoznavanje ust iz digitalnih posnetkov. Pogledali smo obstoječe metode in na podlagi detektorja Viola-Jones ter aktivnih modelov oblike razvili lasten algoritem. Implementiran je bil v jeziku C++ s pomočjo knjižnice OpenCV. Delovanje je bilo preverjeno na ročno označenih slikah. Rezultati so pokazali, da algoritem v nadzorovanem okolju daje spodbudne rezultate. Dobro delovanje smo opazil, ko je oblika ust dovolj splošna in ima oster rob. Slabši rezultati so bili, ko so usta v kotih zelo tanka. Sklepamo lahko, da bi algoritem lahko bil uporabljen v praktični aplikaciji.
Keywords:
računalniški vid
,
prepoznavanje ust
,
aktivni modeli oblike
Place of publishing:
[Maribor
Publisher:
Ž. Leber
Year of publishing:
2015
PID:
20.500.12556/DKUM-54322
UDC:
004.93'1(043.2)
COBISS.SI-ID:
19153430
NUK URN:
URN:SI:UM:DK:IH4HDNDL
Publication date in DKUM:
23.10.2015
Views:
1672
Downloads:
112
Metadata:
Categories:
KTFMB - FERI
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:
LEBER, Žiga, 2015,
AVTOMATSKO PREPOZNAVANJE UST IZ DIGITALNIH POSNETKOV
[online]. Bachelor’s thesis. Maribor : Ž. Leber. [Accessed 26 March 2025]. Retrieved from: https://dk.um.si/IzpisGradiva.php?lang=eng&id=54322
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Secondary language
Language:
English
Title:
AUTOMATIC MOUTH DETECTION IN DIGITAL IMAGES
Abstract:
This thesis is focused on automatic mouth detection in digital images. Existing methods were reviewed and a new algorithm was devised based on the Viola-Jones detector and active shape models. It was implemented with the help of the OpenCV library in the C++ programming language. Performance was tested on manually annotated images. Results have shown that the algorithm gives encouraging results in a controlled environment. Good accuracy has been observed with general mouth shapes with sharp borders. Conversely, images of faces with thin lips at the corners have produced lesser results. It can be concluded that the algorithm has potential to be used in an practical application.
Keywords:
computer vision
,
mouth detection
,
active shape models
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