A hybrid CNN approach for single image depth estimation: A case study

Károly Harsányi, Attila Kiss, András Majdik, T. Szirányi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Three-dimensional scene understanding is an emerging field in many real-world applications. Autonomous driving, robotics, and continuous real-time tracking are hot topics within the engineering society. One essential component of this is to develop faster and more reliable algorithms being capable of predicting depths from RGB images. Generally, it is easier to install a system with fewer cameras because it requires less calibration. Thus, our aim is to develop a strategy for predicting the depth on a single image as precisely as possible from one point of view. There are existing methods for this problem with promising results. The goal of this paper is to advance the state-of-the-art in the field of single-image depth prediction using convolutional neural networks. In order to do so, we modified an existing deep neural network to get improved results. The proposed architecture contains additional side-to-side connections between the encoding and decoding branches.

Original languageEnglish
Title of host publicationMultimedia and Network Information Systems - Proceedings of the 11th International Conference MISSI 2018
EditorsKazimierz Choros, Marek Kopel, Elzbieta Kukla, Andrzej Sieminski
PublisherSpringer Verlag
Pages372-381
Number of pages10
ISBN (Print)9783319986777
DOIs
Publication statusPublished - Jan 1 2019
Event11th International Conference on Multimedia and Network Information Systems, MISSI 2018 - Wroclaw, Poland
Duration: Sep 12 2018Sep 14 2018

Publication series

NameAdvances in Intelligent Systems and Computing
Volume833
ISSN (Print)2194-5357

Other

Other11th International Conference on Multimedia and Network Information Systems, MISSI 2018
CountryPoland
CityWroclaw
Period9/12/189/14/18

Keywords

  • CNN
  • Deep learning
  • Depth estimation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

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  • Cite this

    Harsányi, K., Kiss, A., Majdik, A., & Szirányi, T. (2019). A hybrid CNN approach for single image depth estimation: A case study. In K. Choros, M. Kopel, E. Kukla, & A. Sieminski (Eds.), Multimedia and Network Information Systems - Proceedings of the 11th International Conference MISSI 2018 (pp. 372-381). (Advances in Intelligent Systems and Computing; Vol. 833). Springer Verlag. https://doi.org/10.1007/978-3-319-98678-4_38