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ZENODO
Software . 2022
License: https://opensource.org/licenses/MIT
Data sources: Datacite
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Software . 2024
License: https://opensource.org/licenses/MIT
Data sources: Datacite
ZENODO
Software . 2024
License: https://opensource.org/licenses/MIT
Data sources: Datacite
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DMCP: Depth-Map-Correspondence Algorithm

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 10 Jun 2022Publisher:Zenodo
Authors: Jandeleit, Julian;

doi: 10.5281/zenodo.11242436 , 10.5281/zenodo.6621387 , 10.5281/zenodo.6621388

DMCP: Depth-Map-Correspondence Algorithm

Abstract

Depth-Map-Correspondence Algorithm DMCP aligns the native space of a camera with a different world space. It was developed for the Ushichka Dataset and its thermal cameras. The transformation gets estimated using 4 annotated correspondences which makes DMCP applicable for difficult environments. LANGUAGE: Python INSTALLATION: Unzip dmcp-0.0.1.zip and follow Instructions from Readme.md. VERSION: 0.0.1 corresponds to commit 01d4672 in the respective git repository (https://github.com/ushichka/dmcp). VERSION: 0.0.2 corresponds to commit e7ace21 in the git repository and contains additional data for CVPR Workshop CV4Animals paper. 

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Keywords

pose-estimation, thermal-cameras, ushichka, sensor-fusion, lidar

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selected citations
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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