# Sparse Indoor Camera Positioning with Fiducial Markers
## 5 Conclusions  
This work introduced a novel approach for indoor camera positioning using fiducial markers, uniquely designed to accommodate both overlapping and non-overlapping camera setups in extensive environments. To our knowledge, this is the first method to accurately position any set of fixed cameras in large scenarios, regardless of their overlap status. Our technique employs a mobile camera along with a set of fiducial markers that are strategically placed and moved iteratively in groups. This system facilitates the precise positioning of fixed cameras without overlap. Additionally, we developed an algorithm that automatically identifies markers acting as connectors between these groups, significantly simplifying the camera positioning process.  
Experimental validations across multiple complex scenarios confirm the feasibility and robustness of our system, demonstrating consistent accuracy even in environments without visual overlap while achieving state-of-the-art results in environments with camera overlap. This establishes our method as being capable of incorporating the capabilities of previous methods and additionally handling non-overlapping situations effectively. We believe that the proposed method could significantly enhance automated surveillance systems and improve augmented reality applications within complex indoor environments. However, our system still returns poorer solutions depending on the scale of the real world; therefore, efforts must be made to improve our method.  
Future efforts will focus on refining the automation process for marker detection and enhancing the system's adaptability to dynamically changing environments. We plan to integrate machine learning algorithms to optimize marker placement and improve camera network configurations. Extending this research to outdoor environments could significantly broaden the applicability of our method, potentially impacting urban planning and automated vehicle navigation. Additionally, we aim to explore the feasibility of incorporating total station technology as a complementary or alternative method for camera positioning. Addressing challenges such as adapting the system to varying outdoor lighting and weather conditions will be crucial.  
Conceptualization, P.G.-R., [PERSON]-[PERSON] and [PERSON]-[PERSON]; methodology, [PERSON]-S. and [PERSON]-C.; software, P.G.-R.; validation, P.G.-R., [PERSON]-S. and [PERSON]; formal analysis, R.M.-C.; investigation, P.G.-R.; resources, P.G.-R. and [PERSON]-[PERSON]; data curation, P.G.-R.; writing--original draft preparation, P.G.-R., [PERSON] and [PERSON]; writing--review and editing, [PERSON]-R., [PERSON] and [PERSON]; visualization, P.G.-R.; supervision, [PERSON]; project administration, [PERSON] and [PERSON]; funding acquisition, [PERSON] and [PERSON]. All authors read and agreed to the published version of this manuscript.  
This research has been funded under the project PID2023-147296 NB-I00 of the Ministry of Science, Innovation, and Universities of Spain.  
Not applicable.  
Publicly archived datasets and code can be found at [[https://www.uco.es/investiga/grupos/ava/portfolio/sparse-indoor-camera-positioning/](https://www.uco.es/investiga/grupos/ava/portfolio/sparse-indoor-camera-positioning/)]([https://www.uco.es/investiga/grupos/ava/portfolio/sparse-indoor-camera-positioning/](https://www.uco.es/investiga/grupos/ava/portfolio/sparse-indoor-camera-positioning/)) (accessed on 6 February 2025).  
The authors declare no conflicts of interest.