{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T19:15:58Z","timestamp":1790018158859,"version":"4.0.1"},"reference-count":35,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2026,5,28]],"date-time":"2026-05-28T00:00:00Z","timestamp":1779926400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Nowadays, closed-circuit television (CCTV) cameras are deployed worldwide to monitor movements of humans and other objects to improve the efficiency and safety of societies. Therefore, their proper placement is crucial for achieving effective surveillance coverage. Additionally, their proper placement is significantly important for maximizing visual coverage while reducing installation\/management costs. For this task, digital twin is a useful technology, since it can simulate coverage and blind spots while freely changing camera locations. To implement digital twin, 3D modelling of a structure including a complex room is a key issue. In this paper, we propose a 3D indoor modelling method using 360\u00b0 panoramic images and show its application to a CCTV camera placement optimization. This method constructs a structured 3D model of a target room from captured 360\u00b0 panoramic images using a 3D Gaussian Splatting reconstruction method based on a visual simultaneous localization and mapping (VSLAM) framework. The Inertial Measurement Unit (IMU) is used together to improve the camera position estimation accuracy. The model construction is anchored using a GNSS\/GPS reference to establish global spatial coordinates. As an application of the generated 3D model, optimal locations of a given number of CCTV cameras are determined by combining ray-casting visibility analysis and a greedy optimization algorithm in the virtual environment, maximizing visual coverage while minimizing blind spots and avoiding excessive overlap between camera views. For evaluations, we applied the proposed method to three rooms in Okayama University, Japan, and seven rooms in the Indonesian Institute of Business and Technology, Indonesia. After optimizing camera locations in the virtual environment, the cameras were actually installed in the rooms according to the recommended positions. The performance was evaluated using visibility coverage, blind spot reduction, and Root Mean Squared Error (RMSE) between the estimated and actual camera positions, where promising results were achieved.<\/jats:p>","DOI":"10.3390\/s26113431","type":"journal-article","created":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T17:36:18Z","timestamp":1780076178000},"page":"3431","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A 3D Indoor Modelling Method Using 360\u00b0 Panoramic Images and Its Application to CCTV Camera Placement Optimization"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-6852-4641","authenticated-orcid":false,"given":"Anak Agung Surya","family":"Pradhana","sequence":"first","affiliation":[{"name":"Department of Information and Communication Systems, Okayama University, Okayama 700-8530, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3234-3473","authenticated-orcid":false,"given":"Nobuo","family":"Funabiki","sequence":"additional","affiliation":[{"name":"Department of Information and Communication Systems, Okayama University, Okayama 700-8530, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4697-7322","authenticated-orcid":false,"given":"I Nyoman Darma","family":"Kotama","sequence":"additional","affiliation":[{"name":"Department of Information and Communication Systems, Okayama University, Okayama 700-8530, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4265-0450","authenticated-orcid":false,"given":"Kadek Suarjuna","family":"Batubulan","sequence":"additional","affiliation":[{"name":"Department of Information and Communication Systems, Okayama University, Okayama 700-8530, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7316-7416","authenticated-orcid":false,"given":"Putu","family":"Sugiartawan","sequence":"additional","affiliation":[{"name":"Department of Information and Communication Systems, Okayama University, Okayama 700-8530, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,5,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Darwish, D. (2025). Surveillance Systems Fundamentals. Modern Advancements in Surveillance Systems and Technologies, IGI Global Scientific Publishing.","DOI":"10.4018\/979-8-3693-6996-8.ch001"},{"key":"ref_2","first-page":"7","article-title":"Evaluating the Effectiveness and Ethical Considerations of CCTV Surveillance in Public Spaces: A Cybersecurity Perspective","volume":"3","author":"Sutanto","year":"2024","journal-title":"Int. J. Inf. Syst. Innov. Technol."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Chandrasekaran, M., V, A., K, A.S.K., and Sheoran, N. (2024, January 18\u201319). Enhanced Real-Time Abnormal Event Detection in Video Surveillance for Safety and Security. Proceedings of the 2024 Third International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN), Villupuram, India.","DOI":"10.1109\/ICSTSN61422.2024.10670732"},{"key":"ref_4","unstructured":"Govind, R., Thorat, G., Dhatrak, Y., Bodke, R., and Kale, P. (2024). Intelligent CCTV Surveillance and Alert System. Int. J. Adv. Res. Sci. Commun. Technol. (IJARSCT), 4."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"2353","DOI":"10.47392\/IRJAEH.2025.0348","article-title":"Detection of Criminal Activities and Anomalies through CCTV\u2019s","volume":"3","author":"Sonavane","year":"2025","journal-title":"Int. Res. J. Adv. Eng. Hub (IRJAEH)"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Abe, T., Mori, K., and Tomiyama, H. (2025). Cost Optimization in Selection and Placement of Security Cameras. Proceedings of the 2025 International Technical Conference on Circuits\/Systems, Computers, and Communications (ITC-CSCC), IEEE.","DOI":"10.1109\/ITC-CSCC66376.2025.11137774"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Zhao, L., Zhou, L., Wang, Y., Wang, H., Zhuang, R., and Yao, H. (2023). Optimal Placement Method for Substation Surveillance Cameras Based on Dynamic Programming. Proceedings of the 2023 6th International Conference on Electronics Technology (ICET), IEEE.","DOI":"10.1109\/ICET58434.2023.10211461"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Sekkat, A.R., P\u00e4tzold, M., Wald\u00f6stl, D., Sawade, O., and Matthes, E. (2023). Camera placement for parking surveillance applications using a two-step digital twin approach. Proceedings of the 2023 IEEE International Conference on Omni-Layer Intelligent Systems (COINS), IEEE.","DOI":"10.1109\/COINS57856.2023.10189276"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Isoda, T., Miyoshi, T., and Yamazaki, T. (2023). Digital Twin Platform for Road Traffic Using CARLA Simulator. Proceedings of the 2023 IEEE 13th International Conference on Consumer Electronics-Berlin (ICCE-Berlin), IEEE.","DOI":"10.1109\/ICCE-Berlin58801.2023.10375617"},{"key":"ref_10","first-page":"555912","article-title":"A Mathematical Analysis of Blind Spots within Enclosed Spaces","volume":"15","author":"Song","year":"2025","journal-title":"Civ. Eng. Res. J."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Wang, Y., Chen, H.Y., and Sheng, M. (2024). Simulation of Camera Visual Range Based on Three-dimensional Model. Proceedings of the 2024 International Conference on Power, Electrical Engineering, Electronics and Control (PEEEC), IEEE.","DOI":"10.1109\/PEEEC63877.2024.00160"},{"key":"ref_12","first-page":"368","article-title":"Visual-SLAM based 3-dimensional modelling of indoor environments","volume":"9","year":"2024","journal-title":"Int. J. Eng. Geosci."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"379","DOI":"10.5194\/isprs-archives-XLVIII-2-W8-2024-379-2024","article-title":"3D indoor modeling with low-cost RGB-D camera and iPad Pro: A Comparative Study","volume":"XLVIII-2\/W8-2024","author":"Rached","year":"2024","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_14","first-page":"356","article-title":"3D Indoor Reconstruction Based on Spatial Layout Estimation Using Panoramic Inspection Video from Building Sites","volume":"Volume 22","author":"Cheng","year":"2025","journal-title":"Proceedings of the Sixth International Conference on Civil and Building Engineering Informatics"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Zhang, J., Wang, S., Zhang, L., and Liu, M. (2024). Immersive Dramatic Space 3D Layout Using Panoramic Image Reconstruction Algorithm. Proceedings of the 2024 Third International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE), IEEE.","DOI":"10.1109\/ICDCECE60827.2024.10548046"},{"key":"ref_16","first-page":"894","article-title":"BIM-based framework for optimization of CCTV surveillance in buildings","volume":"29","author":"Aziz","year":"2024","journal-title":"J. Inf. Technol. Constr. (ITCON)"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1172","DOI":"10.1109\/TSMC.2022.3194209","article-title":"A Generic and Scalable Approach to Maximize Coverage in Diverse Indoor and Outdoor Multicamera Surveillance Scenarios","volume":"53","author":"Suresh","year":"2023","journal-title":"IEEE Trans. Syst. Man. Cybern. Syst."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"096301","DOI":"10.1088\/1361-6501\/ad4f02","article-title":"An end-to-end learning framework for visual camera relocalization using RGB and RGB-D images","volume":"35","author":"Zhang","year":"2024","journal-title":"Meas. Sci. Technol."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Chen, X., and Fan, G. (2025). Probabilistic Perspective-n-Lines for Indoor Camera Pose Estimation. Proceedings of the 2025 IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), IEEE.","DOI":"10.1109\/CVPRW67362.2025.00451"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"61601","DOI":"10.1109\/ACCESS.2022.3176817","article-title":"A Multiresolution Approach for Large Real-World Camera Placement Optimization Problems","volume":"10","author":"Puligandla","year":"2022","journal-title":"IEEE Access"},{"key":"ref_21","unstructured":"Sattineni, A.A.U., Azhar, S.A.U., and Castro, D.G.T.U. (2016). Optimizing Surveillance Camera Placement in Buildings Using BIM. Proceedings of the 33rd International Symposium on Automation and Robotics in Construction (ISARC), International Association for Automation and Robotics in Construction (IAARC)."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"26574","DOI":"10.1109\/JSEN.2024.3424307","article-title":"Exploring Sensor Placement Optimization in Point Cloud-Derived Environment Models","volume":"24","author":"Banov","year":"2024","journal-title":"IEEE Sens. J."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"68","DOI":"10.56415\/csjm.v33.04","article-title":"Integrating Recurrent Neural Networks and Loss Function Optimization for Efficient Indoor Camera Positioning","volume":"33","author":"Alam","year":"2025","journal-title":"Comput. Sci. J. Mold."},{"key":"ref_24","first-page":"138","article-title":"Multi-Objective Optimization of CCTV Placement: A Case Study at Bukidnon State University","volume":"22","author":"Agurob","year":"2024","journal-title":"Mindanao J. Sci. Technol."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1499","DOI":"10.1177\/00202940231163935","article-title":"Camera Placement Optimization for CCTV in Rail Transit Using BIM","volume":"56","author":"Xie","year":"2023","journal-title":"Meas. Control"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Li, B., and Li, C. (2025). Optimization of Video Surveillance System Deployment Based on Space Syntax and Deep Reinforcement Learning. Electronics, 14.","DOI":"10.3390\/electronics14010038"},{"key":"ref_27","first-page":"1","article-title":"Exploration of Digital Communication Mechanism of Film and Television Media Industry in the Background of Artificial Intelligence","volume":"9","author":"Pan","year":"2023","journal-title":"Appl. Math. Nonlinear Sci."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Urrutia-Azcona, K., Bonetti, V., Mizanur, M., Janssen, N., Buckley, N., De Wit, M., Murray, K., and Byrne, N. (2026). Co-Creating Climate-Resilient Streets: Digital Twin-Based Simulations for Outdoor Thermal Comfort. Smart Cities, 9.","DOI":"10.3390\/smartcities9020039"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Qin, K., Li, J., Zlatanova, S., Wu, H., Wu, H., Gao, Y., Zhou, D., Li, Y., Shen, S., and Qu, X. (2026). VGGT-Geo: Probabilistic Geometric Fusion of Visual Geometry Grounded Transformer Priors for Robust Dense Indoor SLAM. ISPRS Int. J. -Geo-Inf., 15.","DOI":"10.3390\/ijgi15020085"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Tejada Peralta, A.F.P., Bakzadeh, R., Siahidouzazar, S., and Roghanchi, P. (2026). Automated Object Detection and Change Quantification in Underground Mines Using LiDAR Point Clouds and 360\u00b0 Image Processing. Appl. Sci., 16.","DOI":"10.3390\/app16052337"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Han, J., Yoon, S., Kang, M., and Kim, T. (2025). Approach to Enhancing Panoramic Segmentation in Indoor Construction Sites Based on a Perspective Image Segmentation Foundation Model. Appl. Sci., 15.","DOI":"10.3390\/app15094875"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Xu, Y., Liu, Y., Li, H., Wang, L., and Ai, J. (2024). A Deep Learning Approach of Intrusion Detection and Tracking with UAV-Based 360\u00b0 Camera and 3-Axis Gimbal. Drones, 8.","DOI":"10.3390\/drones8020068"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Baysal, D. (2023). Assessment of Vehicular Vision Obstruction Due to Driver-Side B-Pillar and Remediation with Blind Spot Eliminator. Ssrn Electron. J., 1\u201331.","DOI":"10.4271\/2023-01-5056"},{"key":"ref_34","first-page":"45","article-title":"Evaluation of Coordinate Position Precision Using GNSS NEO SERIES and GSM SIM 7000E Modules","volume":"8","author":"Kusuma","year":"2024","journal-title":"J. Appl. Geomat. Civ. Eng. (JAGI)"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1061\/(ASCE)SU.1943-5428.0000075","article-title":"Accuracy Evaluation of Terrestrial LIDAR and Multibeam Sonar Systems Mounted on a Survey Vessel","volume":"138","author":"Dix","year":"2012","journal-title":"J. Surv. Eng."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/26\/11\/3431\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T09:36:51Z","timestamp":1780479411000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/26\/11\/3431"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5,28]]},"references-count":35,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2026,6]]}},"alternative-id":["s26113431"],"URL":"https:\/\/doi.org\/10.3390\/s26113431","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,5,28]]}}}