@inproceedings{baltzer2025geogames,
    author = {Baltzer, Dorian and Douglas, Shannon and Tiemann, Inga and Haunert, Jan-Henrik},
    booktitle = {Proceedings of the 2nd Geogames Symposium: Connecting Communities Through Games and Play},
    isbn = {978-1-910963-87-6},
    title = {Interactive {G}eovisualization in {E}ducational {E}scape {G}ames: {A}ssessing {2D} vs. {3D} {D}esigns on {A}nimal {W}elfare {A}wareness},
    url = {https://researchrepository.ucd.ie/entities/publication/8d6f0a4c-638c-4aa0-8790-6489893d30d7},
    year = {2025}
}

Recent developments in consumer-grade panoramic cameras led to new possibilities in creating virtual tours, e.g., through museums or real estate. Most current approaches for the creation of these tours are based on manual generation of navigable links between the images. We consider cases where large numbers of georeferenced images are taken by multiple users and introduce an approach for automatically generating a graph structure that links the images in a reasonable network while sorting out redundant data. Our approach does not expect a trajectory of temporally related points but merely an incoherent point cloud, e.g., from crowdsourcing of many different contributors. We expand our methodology by a visualization approach offering in-image navigation, realized through interactive links pointing towards neighbored images. Our method delivers a virtual tour with adjustable density on and apart from road networks. We compared the output of our algorithm to human-made virtual tour graphs and were able to verify a high similarity, which approves the hypothesis that automatically generated virtual tours can be intuitive for users.

doi:10.1007/s41651-025-00228-1

@article{baltzer2025graph,
    abstract = {Recent developments in consumer-grade panoramic cameras led to new possibilities in creating virtual tours, e.g., through museums or real estate. Most current approaches for the creation of these tours are based on manual generation of navigable links between the images. We consider cases where large numbers of georeferenced images are taken by multiple users and introduce an approach for automatically generating a graph structure that links the images in a reasonable network while sorting out redundant data. Our approach does not expect a trajectory of temporally related points but merely an incoherent point cloud, e.g., from crowdsourcing of many different contributors. We expand our methodology by a visualization approach offering in-image navigation, realized through interactive links pointing towards neighbored images. Our method delivers a virtual tour with adjustable density on and apart from road networks. We compared the output of our algorithm to human-made virtual tour graphs and were able to verify a high similarity, which approves the hypothesis that automatically generated virtual tours can be intuitive for users.},
    author = {Baltzer, Dorian and Naumann, Alexander and Rosenberg, Stephan and Haunert, Jan-Henrik},
    doi = {10.1007/s41651-025-00228-1},
    journal = {Journal of Geovisualization and Spatial Analysis},
    pages = {},
    publisher = {Springer Nature},
    title = {Graph Construction and Interactive Visualization for Virtual Tours Based on Redundant Panoramic Image Collections},
    url = {https://link.springer.com/article/10.1007/s41651-025-00228-1},
    volume = {9},
    year = {2025}
}

Livestock production requires a thorough understanding of animal welfare to increase productivity and ensure appropriate housing conditions. The expanding availability of consumer-grade virtual and augmented reality devices opens new possibilities for precision livestock farming (PLF), where sensor technology traditionally monitors real-time animal data. In poultry farming, monitoring each bird individually is often not economically feasible due to the large flock sizes. To address this issue, we propose a novel method to evaluate housing conditions by focusing on the visual and temperature preferences of domestic chickens, considering these factors within a broader environmental context. Chickens perceive light at a wider range of wavelengths than humans, which significantly influences their behavior. Additionally, temperature variations, such as heat leaks and accumulations, can contribute to stress and negative behaviors in the flock. We developed a device comprising smart glasses equipped with specialized cameras to capture thermal infrared, ultraviolet, and visible RGB (red, green, blue) light, alongside real-time user position tracking. Points of interest (POIs) can be added to the logged tracking data along with captured content. The data collected by the glasses can be used to create virtual tours embedded in a 3D model of the barn, providing a comprehensive view of on-site conditions. We also introduce a streamlined pipeline for building these virtual tours using the Unity game engine, making the content accessible for agricultural education. This approach enables users to remotely gain insights into the housing conditions of poultry without needing a physical visit, enhancing both learning and engagement in animal welfare practices.

doi:10.1016/j.atech.2025.100786

@article{baltzer2025smart,
    abstract = {Livestock production requires a thorough understanding of animal welfare to increase productivity and ensure appropriate housing conditions. The expanding availability of consumer-grade virtual and augmented reality devices opens new possibilities for precision livestock farming (PLF), where sensor technology traditionally monitors real-time animal data. In poultry farming, monitoring each bird individually is often not economically feasible due to the large flock sizes. To address this issue, we propose a novel method to evaluate housing conditions by focusing on the visual and temperature preferences of domestic chickens, considering these factors within a broader environmental context. Chickens perceive light at a wider range of wavelengths than humans, which significantly influences their behavior. Additionally, temperature variations, such as heat leaks and accumulations, can contribute to stress and negative behaviors in the flock. We developed a device comprising smart glasses equipped with specialized cameras to capture thermal infrared, ultraviolet, and visible RGB (red, green, blue) light, alongside real-time user position tracking. Points of interest (POIs) can be added to the logged tracking data along with captured content. The data collected by the glasses can be used to create virtual tours embedded in a 3D model of the barn, providing a comprehensive view of on-site conditions.
We also introduce a streamlined pipeline for building these virtual tours using the Unity game engine, making the content accessible for agricultural education. This approach enables users to remotely gain insights into the housing conditions of poultry without needing a physical visit, enhancing both learning and engagement in animal welfare practices.},
    author = {Baltzer, Dorian and Douglas, Shannon and Haunert, Jan-Henrik and Dehbi, Youness and Tiemann, Inga},
    doi = {10.1016/j.atech.2025.100786},
    journal = {Smart Agricultural Technology},
    pages = {100786},
    publisher = {Elsevier},
    title = {Smart Glasses in the Chicken Barn: Enhancing Animal Welfare Through Mixed Reality},
    url = {https://www.sciencedirect.com/science/article/pii/S2772375525000206?via%3Dihub},
    volume = {10},
    year = {2025}
}

doi:10.5281/ZENODO.13833373

@techreport{baltzer2024techreport,
    author = {Baltzer, Dorian},
    doi = {10.5281/ZENODO.13833373},
    organization = {University of Bonn},
    title = {VisioChick: Smart Glasses for assessing poultry housing conditions - Technical Instruction Manual},
    url = {https://zenodo.org/records/13833373},
    year = {2024}
}

doi:10.5194/ica-abs-7-8-2024

@article{baltzer2024automatically,
    author = {Baltzer, Dorian and Naumann, Alexander and Rosenberg, Stephan and Haunert, Jan-Henrik},
    doi = {10.5194/ica-abs-7-8-2024},
    journal = {Abstracts of the ICA},
    pages = {8},
    publisher = {Copernicus Publications G{\"o}ttingen, Germany},
    title = {Automatically generating virtual tours based on dense sets of 360° imagery},
    url = {https://ica-abs.copernicus.org/articles/7/8/2024/ica-abs-7-8-2024.pdf},
    volume = {7},
    year = {2024}
}

Due to the global climate change and increasing traffic volumes in cities, a shift from individual to public and multimodal transport is aspired. Travel time is one of the most important aspects for many people when choosing their mode of trans- portation. This leads to the requirement that changes in travel times have to be considered when planning new public trans- port infrastructure. This research paper presents and compares different techniques for visualizing the impact of new lines in existing public transport networks on travel times. The general approach of simulating timetable data and calculating intermodal travel times considering public transport and walking is being applied to two current infrastructure projects in the city of Bonn and the surrounding region. The created maps generally aim to visualize the spread in travel times between existing and extended transportation networks discretized by different spatial units such as rectangles or postal code areas. In comparison to other common methods which typically require two maps for two different scenarios (e.g. in case of isochro- nes), our approach gives the opportunity to combine all relevant information within one map. It is also shown how to apply bivariate choropleth maps for displaying travel times and how to visualize improvements in the accessibility of multiple target points of interest at once.

doi:10.1007/s42489-024-00167-9

@article{Baltzer2024,
    abstract = {Due to the global climate change and increasing traffic volumes in cities, a shift from individual to public and multimodal
transport is aspired. Travel time is one of the most important aspects for many people when choosing their mode of trans-
portation. This leads to the requirement that changes in travel times have to be considered when planning new public trans-
port infrastructure. This research paper presents and compares different techniques for visualizing the impact of new lines
in existing public transport networks on travel times. The general approach of simulating timetable data and calculating
intermodal travel times considering public transport and walking is being applied to two current infrastructure projects in
the city of Bonn and the surrounding region. The created maps generally aim to visualize the spread in travel times between
existing and extended transportation networks discretized by different spatial units such as rectangles or postal code areas. In
comparison to other common methods which typically require two maps for two different scenarios (e.g. in case of isochro-
nes), our approach gives the opportunity to combine all relevant information within one map. It is also shown how to apply
bivariate choropleth maps for displaying travel times and how to visualize improvements in the accessibility of multiple
target points of interest at once.},
    author = {Baltzer, Dorian and Haunert, Jan-Henrik and Forsch, Axel},
    doi = {10.1007/s42489-024-00167-9},
    journal = {KN - Journal of Cartography and Geographic Information},
    pages = {107--119},
    publisher = {Springer},
    title = {Visualizing the Influence of New Public Transport Infrastructure on Travel Times},
    url = {https://link.springer.com/article/10.1007/s42489-024-00167-9},
    volume = {74},
    year = {2024}
}

doi:10.14627/gis.Science.2024.2.1

@article{baltzer2024kart,
    author = {Baltzer, Dorian},
    doi = {10.14627/gis.Science.2024.2.1},
    journal = {gis.Science},
    pages = {39--45},
    publisher = {Wichmann},
    title = {Kartierung des {ÖPNV} der {Z}ukunft: {M}ethodik zur {V}orhersage von {R}eisezeitgewinnen durch neue {L}inien in bestehenden {N}etzen},
    url = {https://gispoint.de/artikelarchiv/gis/2024/gisscience-ausgabe-22024/8158-kartierung-des-oepnv-der-zukunft-methodik-zur-vorhersage-von-reisezeitgewinnen-durch-neue-linien-in-bestehenden-netzen.html},
    volume = {2},
    year = {2024}
}