Naslov
Depth from Mono Accuracy Analysis by Changing Camera Parameters in the CARLA simulator

Autori
Gršković Zvonimir ; Peršić, Juraj ; Marković Ivan ; Petrović, Ivan

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

Izvornik
International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) / - , 2021, 1-6

Skup
44th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO 2021)

Mjesto i datum
Opatija, Hrvatska, 27.09.2021. - 01.10.2021

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Monocular depth estimation ; Self-supervised training ; CARLA simulator

Sažetak
Depth estimation is an important task in robotics and autonomous driving. By estimating depth and relying only on a single camera, it is no longer necessary to add and calibrate additional sensors – usually a second camera. However, such an approach requires training on extensive datasets and obtaining real-world datasets is time consuming and costly. Given that, using photorealistic simulators can be beneficial, since a multitude of various scenes can be created. In this paper we present an approach to training a deep neural network based on the ResNet architecture for estimating depth from a single camera. We target road vehicle scenes and use the CARLA simulator. We evaluate the trained network on the real-world KITTI dataset images and in the CARLA simulator. In the simulated experiments, we compare the performance with respect to the changes in camera intrinsic and extrinsic calibration parameters with respect to the ego vehicle frame.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo, Temeljne tehničke znanosti

POVEZANOST RADA