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master's thesis
Sustav za detekciju pješaka
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2014. urn:nbn:hr:168:384828
Ćuk, Daniel
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Ćuk, D. (2014). Sustav za detekciju pješaka (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:384828

Ćuk, Daniel. "Sustav za detekciju pješaka." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2014. https://urn.nsk.hr/urn:nbn:hr:168:384828

Ćuk, Daniel. "Sustav za detekciju pješaka." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2014. https://urn.nsk.hr/urn:nbn:hr:168:384828

Ćuk, D. (2014). 'Sustav za detekciju pješaka', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 26 December 2024, https://urn.nsk.hr/urn:nbn:hr:168:384828

Ćuk D. Sustav za detekciju pješaka [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2014 [cited 2024 December 26] Available at: https://urn.nsk.hr/urn:nbn:hr:168:384828

D. Ćuk, "Sustav za detekciju pješaka", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2014. Available at: https://urn.nsk.hr/urn:nbn:hr:168:384828

Metadata
TitleSustav za detekciju pješaka
Title (english)Pedestrian detection system
AuthorDaniel Ćuk
MentorZoran Kalafatić (mentor)
Committee memberZoran Kalafatić (predsjednik povjerenstva)
Committee memberSiniša Šegvić (član povjerenstva)
Committee memberTomislav Hrkać (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2014-07-15, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Povećanje sigurnosti u prometu težak je zadatak koji privlači sve veći broj znanstvenika. Sustav za detekciju pješaka uvelike bi pridonio sigurnosti pješaka u prometu. Vozačima bi olakšao uočavanje pješaka te samim time pridonio lakšem i bezbrižnijem sudjelovanju u prometu. U ovome radu opisane su tri vrste detektora pješaka te uspoređene njihove performanse: kaskada klasifikatora s pravokutnim značajkama, klasifikator SVM sa značajkama HoG te kaskada klasifikatora SVM s opisnikom značajki HoG. Kaskade su učene varijacijama algoritma AdaBoost. Algoritam AdaBoost također je upotrijebljen za odabir najrelevantnijih značajki iz velikog skupa značajki. Također je razvijen sustav s grafičkim sučeljem za detekciju pješaka koji koristi sve tri vrste detektora. Sustav radi na slikama ili videu.
Abstract (english)
Improvement of traffic safety is a difficult task that attracts more and more scientists. Pedestrian detection system would considerably contribute to pedestrian traffic safety. It would make the detection of pedestrians easier to drivers and at the same time would contribute to easier and careless traffic engagement. Three types of pedestrian detection are described in this paper and their characteristics are compared: cascade of classifiers with rectangular features, classifier SVM with HoG features and cascade of SVM classifiers with HoG features descriptor. The cascades are learned with variations of AdaBoost algorithm. The AdaBoost algorithm is also used to select the most relevant features from larger set of features. The system with graphical interface for pedestrian detection using all three types of detector is also developed. The system works on images or video.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:384828
Study programmeTitle: Computing
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsClosed access
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Created on2018-02-06 08:22:21