Details
| Original language | English |
|---|---|
| Title of host publication | Pattern Recognition - 40th German Conference, GCPR 2018, Proceedings |
| Editors | Andrés Bruhn, Mario Fritz, Thomas Brox |
| Publisher | Springer Verlag |
| Pages | 407-421 |
| Number of pages | 15 |
| ISBN (print) | 9783030129385 |
| Publication status | Published - 9 Oct 2018 |
| Event | 40th German Conference on Pattern Recognition, GCPR 2018 - Stuttgart, Germany Duration: 9 Oct 2018 → 12 Oct 2018 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 11269 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (electronic) | 1611-3349 |
Abstract
In this paper, we propose a new approach for dense depth estimation based on multimodal stereo images. Our approach employs a combined cost function utilizing robust metrics and a transformation to an illumination independent representation. Additionally, we present a confidence based weighting scheme which allows a pixel-wise weight adjustment within the cost function. We demonstrate the capabilities of our approach using RGB- and thermal images. The resulting depth maps are evaluated by comparing them to depth measurements of a Velodyne HDL-64E LiDAR sensor. We show that our method outperforms current state of the art dense matching methods regarding depth estimation based on multimodal input images.
ASJC Scopus subject areas
- Mathematics(all)
- Theoretical Computer Science
- Computer Science(all)
- General Computer Science
Cite this
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Pattern Recognition - 40th German Conference, GCPR 2018, Proceedings. ed. / Andrés Bruhn; Mario Fritz; Thomas Brox. Springer Verlag, 2018. p. 407-421 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11269 LNCS).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Multimodal Dense Stereo Matching
AU - Mehltretter, Max
AU - Kleinschmidt, Sebastian P.
AU - Wagner, Bernardo
AU - Heipke, Christian
N1 - Funding information:. This work was supported by the German Research Foundation (DFG) as a part of the Research Training Group i.c.sens [GRK2159] and the MOBILISE initiative of the Leibniz Universität Hannover and TU Braunschweig.
PY - 2018/10/9
Y1 - 2018/10/9
N2 - In this paper, we propose a new approach for dense depth estimation based on multimodal stereo images. Our approach employs a combined cost function utilizing robust metrics and a transformation to an illumination independent representation. Additionally, we present a confidence based weighting scheme which allows a pixel-wise weight adjustment within the cost function. We demonstrate the capabilities of our approach using RGB- and thermal images. The resulting depth maps are evaluated by comparing them to depth measurements of a Velodyne HDL-64E LiDAR sensor. We show that our method outperforms current state of the art dense matching methods regarding depth estimation based on multimodal input images.
AB - In this paper, we propose a new approach for dense depth estimation based on multimodal stereo images. Our approach employs a combined cost function utilizing robust metrics and a transformation to an illumination independent representation. Additionally, we present a confidence based weighting scheme which allows a pixel-wise weight adjustment within the cost function. We demonstrate the capabilities of our approach using RGB- and thermal images. The resulting depth maps are evaluated by comparing them to depth measurements of a Velodyne HDL-64E LiDAR sensor. We show that our method outperforms current state of the art dense matching methods regarding depth estimation based on multimodal input images.
UR - http://www.scopus.com/inward/record.url?scp=85063499082&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-12939-2_28
DO - 10.1007/978-3-030-12939-2_28
M3 - Conference contribution
AN - SCOPUS:85063499082
SN - 9783030129385
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 407
EP - 421
BT - Pattern Recognition - 40th German Conference, GCPR 2018, Proceedings
A2 - Bruhn, Andrés
A2 - Fritz, Mario
A2 - Brox, Thomas
PB - Springer Verlag
T2 - 40th German Conference on Pattern Recognition, GCPR 2018
Y2 - 9 October 2018 through 12 October 2018
ER -