# Sparse Indoor Camera Positioning with Fiducial Markers  
[PERSON]  
1 Departamento de Informatica y Analisis Numerico, Edificio Einstein, Campus de Rabanales, Universidad de Cordoba, 14071 Cordoba, Spain; [EMAIL_ADDRESS] (R.M.-C.)1 Departamento de Teoria de la Senal y Comunicaciones y Sistemas Telematicos y Computacion, Campus de Fuentabrada, Universidad Rey Juan Carlos, 28942 Fuenlabrada, Spain; [EMAIL_ADDRESS]  
[PERSON]  
2 Departamento de Teoria de la Senal y Comunicaciones y Sistemas Telematicos y Computacion, Campus de Fuentabrada, Universidad Rey Juan Carlos, 28942 Fuenlabrada, Spain; [EMAIL_ADDRESS]  
[PERSON]  
1 Departamento de Informatica y Analisis Numerico, Edificio Einstein, Campus de Rabanales, Universidad de Cordoba, 14071 Cordoba, Spain; [EMAIL_ADDRESS] (R.M.-C.)1 Departamento de Informatica y Analisis Numerico, Edificio Einstein, Campus de Rabanales, Universidad de Cordoba, 14071 Cordoba, Spain; [EMAIL_ADDRESS] (R.M.-C.)1 Departamento de Informatica y Analisis Numerico, Edificio Einstein, Campus de Rabanales, Universidad de Cordoba, 14071 Cordoba, Spain; [EMAIL_ADDRESS] (R.M.-S.)1 Departamento de Informatica y Analisis Numerico, Edificio Einstein, Campus de Rabanales, Universidad de Cordoba, 14071 Cordoba, Spain; [EMAIL_ADDRESS] (R.M.-C.)1 Departamento de Informatica y Analisis Numerico, Edificio Einstein, Campus de Rabanales, Universidad de Cordoba, 14071 Cordoba, Spain; mendina@uco. camera overlap cannot be guaranteed due to environmental constraints or the need for wider spatial coverage [7; 8; 9]. A representation of this problem is shown in Figure 1. Being able to accurately position cameras without relying on overlapping fields of view would be highly beneficial in various scenarios, such as surveillance systems and indoor robotic navigation [10; 11; 12; 13]. Several solutions have been proposed to address the challenges associated with fixed camera positioning. Feature-based approaches, which identify and rely on distinctive points or features in the scene, have demonstrated effectiveness in environments with rich visual details. Techniques such as structure from motion (SfM) [14; 15] and simultaneous localization and mapping (SLAM) [16; 17] have been foundational in this domain, leveraging feature detection and matching across overlapping images to estimate camera poses. These methods have driven significant advancements in computer vision by capitalizing on the geometric and photometric relationships inherent in overlapping visual data. Despite their success, these methodologies face substantial limitations in scenarios where camera views do not overlap. In such cases, the absence of essential correspondences between views severely hampers pose estimation. To address this limitation, several methods designed for non-overlapping camera setups have been developed [6; 18]. While these approaches represent progress toward solving the problem, they encounter significant challenges in achieving robust and reliable performance in non-overlapping scenarios, leaving room for further innovation and improvement in this area. Marker-based approaches provide an alternative solution for pose estimation by relying on the strategic placement of predefined markers within the scene [4; 5]. These methods have demonstrated significant robustness in controlled environments where markers remain consistently visible. However, their applicability is significantly reduced in non-overlapping camera setups, as the absence of shared markers across distinct viewpoints hinders effective pose estimation. Although advancements such as those proposed by [PERSON] et al. [19] have explored this domain, the problem remains unresolved, particularly in addressing the challenges posed by complex and large-scale scenarios. This limitation underscores the inherent constraints of both feature-based and marker-based approaches,  
Figure 1: **Sparse camera representation. ** A depiction of a floor setup with a common arrangement of surveillance cameras. The positions of the cameras and their fields of view are depicted in blue.