Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Max Mehltretter"'
Autor:
Viktor Wendel, Marc-André Bär, Robert Hahn, Benedict Jahn, Max Mehltretter, Stefan Göbel, Ralf Steinmetz
Publikováno v:
EAI Endorsed Transactions on Serious Games, Vol 1, Iss 4, Pp 1-10 (2015)
One major Serious Games challenge is adaptation of game-based learning environments towards the needs of players with heterogeneous player and learner traits. For both an instructor or an algorithmic adaptation mechanism it is vital to have knowledge
Externí odkaz:
https://doaj.org/article/5679d8271d944aa7b44b8d9533d43368
Autor:
Max Mehltretter
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. :69-78
The necessity to identify errors in the context of image-based 3D reconstruction has motivated the development of various methods for the estimation of uncertainty associated with depth estimates in recent years. Most of these methods exclusively est
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9b6c88654f9a27f6c47b8ac56297e56a
https://doi.org/10.5194/isprs-annals-v-2-2022-69-2022
https://doi.org/10.5194/isprs-annals-v-2-2022-69-2022
Autor:
Max Mehltretter, Z. Zhong
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol V-2-2021, Pp 17-26 (2021)
The ability to identify erroneous depth estimates is of fundamental interest. Information regarding the aleatoric uncertainty of depth estimates can be, for example, used to support the process of depth reconstruction itself. Consequently, various me
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::33ec30793e1dbbc834a60ed190622560
https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/V-2-2021/17/2021/isprs-annals-V-2-2021-17-2021.pdf
https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/V-2-2021/17/2021/isprs-annals-V-2-2021-17-2021.pdf
Autor:
Max Mehltretter, Christian Heipke
Publikováno v:
ISPRS Journal of Photogrammetry and Remote Sensing. 171:63-75
Motivated by the need to identify erroneous disparity estimates, various methods for the estimation of aleatoric uncertainty in the context of dense stereo matching have been presented in recent years. Especially, the introduction of deep learning ba
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e5c42a8d492495cc67990bffe7a44dc4
https://doi.org/10.1016/j.isprsjprs.2020.11.003
https://doi.org/10.1016/j.isprsjprs.2020.11.003
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol V-2-2020, Pp 151-159 (2020)
In the present work, an uncertainty-driven geometry-based regularisation for the task of dense stereo matching is presented. The objective of the regularisation is the reduction of ambiguities in the depth reconstruction process, which exist due to t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a5864bf16e57ec6314a727af1f7e64e0
https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/V-2-2020/151/2020/isprs-annals-V-2-2020-151-2020.pdf
https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/V-2-2020/151/2020/isprs-annals-V-2-2020-151-2020.pdf
Autor:
Christian Heipke, Max Mehltretter
Publikováno v:
ICCV Workshops
Due to its capability to identify erroneous disparity assignments in dense stereo matching, confidence estimation is beneficial for a wide range of applications, e.g. autonomous driving, which needs a high degree of confidence as mandatory prerequisi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3576a2b0666f92d69ef3927832de662c
http://arxiv.org/abs/1905.07287
http://arxiv.org/abs/1905.07287
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030129385
GCPR
GCPR
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. Addition
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2855950508e6b694c0556ef9cb012c9a
https://doi.org/10.1007/978-3-030-12939-2_28
https://doi.org/10.1007/978-3-030-12939-2_28
Autor:
Sebastian P. Kleinschmidt, Holger Blume, Christian Heipke, Max Mehltretter, Nicolai Behmann, Betnardo Wagner
Publikováno v:
NORCAS
Multiple modalities for stereo matching are beneficial for robust path estimation and actioning of autonomous robots in harsh environments, e.g. in the presence of smoke and dust. In order to combine the information resulting from the different modal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2bff073629349dd9e84c5e5e9e5d8b8c
https://doi.org/10.1109/norchip.2018.8573526
https://doi.org/10.1109/norchip.2018.8573526