Naslov
Object detection and object tracking in front of the vehicle using front view camera

Autori
Ciberlin, Juraj ; Grbić, Ratko ; Teslić, Nikola ; Pilipović, Miloš

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
2019 Zooming Innovation in Consumer Technologies Conference (ZINC) / - : Institute of Electrical and Electronics Engineers (IEEE), 2019, 27-32

Skup
Zooming Innovation in Consumer Technologies Conference (ZINC 2019)

Mjesto i datum
Novi Sad, Srbija, 29.05.2019. - 30.05.2019

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
object detection ; object tracking ; autonomous vehicles ; Viola-Jones algorithm ; advanced driver assistance systems

Sažetak
Modern vehicles are equipped with the different systems that help driver in the driving process ensuring safer and more comfortable driving. These systems are called Advanced Driver Assistance Systems (ADAS) and are step toward fully autonomous driving. The integral part of autonomous driving is an object detection and tracking by using front view camera which provides necessary information for emergency braking, collision avoidance, path planning, etc. In this paper, one possible approach to object detection and tracking in autonomous driving is presented. Two object detection methods are implemented and tested: Viola-Jones algorithm and YOLOv3. The Viola-Jones algorithm is used to create object detectors which detections are tracked in a video sequence. Nine object detectors were trained and they are divided into four groups (vehicle detectors, pedestrian detector, traffic light detector and traffic sign detectors). In second case, the YOLOv3 model was used for object detection. Both methods are evaluated in terms of accuracy and processing speed. For the purpose of object tracking, Median Flow tracking method and correlation tracking method are implemented and evaluated.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

POVEZANOST RADA