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RGB-IR Vision for 3D Scene Analysis and Thermal Assessment

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: 20 September 2026 | Viewed by 1026

Editor


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Guest Editor
The Institute of Radioelectronics and Multimedia Technology, University of Warsaw, Warsaw, Poland
Interests: computer vision; image processing; deep learning

Special Issue Information

Dear Colleagues,

In recent years, the fusion of RGB and infrared (IR) imaging technologies has opened new frontiers in the 3D analysis of real-world scenes, especially in thermal diagnostics and energy efficiency assessments. For this Special Issue, we invite contributions at the intersection of multispectral vision, 3D reconstruction, and thermal analysis, with a focus on the calibration, registration, and interpretation of data acquired using RGB and long-wave infrared cameras.

We particularly welcome papers on the applications of low-cost, mobile imaging systems—such as those based on Raspberry Pi or similar platforms—in the analysis of buildings and infrastructure. These may include heat loss detection, thermal bridge identification, defect localization, and the data-driven estimation of residential structures’ energy efficiency.

The topics of interest include (but are not limited to) the following:

- RGB-IR camera calibration for multispectral 3D scene acquisition;
- Stereo and depth estimation using combined visible and thermal data;
- Thermal-emissive feature detection and semantic segmentation;
- The radiometric alignment and calibration of LWIR sensors;
- Low-cost embedded systems for thermal monitoring and smart inspection;
- Machine learning methods for the fusion and interpretation of RGB and IR images;
- Applications in energy loss estimation and building diagnostics;
- Mobile vision systems for real-time environmental monitoring;
- Data collection protocols and benchmark datasets for RGB-IR fusion.

Prof. Dr. Władysław Skarbek
Guest Editor

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • RGB
  • 3D analysis
  • multispectral vision
  • 3D reconstruction
  • thermal analysis

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Published Papers (1 paper)

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Research

30 pages, 3936 KB  
Article
Camera Pose Revisited
by Władysław Skarbek, Michał Salamonowicz and Michał Król
Appl. Sci. 2026, 16(6), 2690; https://doi.org/10.3390/app16062690 - 11 Mar 2026
Cited by 1 | Viewed by 566
Abstract
Estimating the position and orientation of a camera with respect to an observed scene remains a fundamental problem in computer vision, particularly in calibration procedures and multi-sensor vision systems. This paper revisits the planar Perspective–n–Point (PnP) problem with emphasis on rotation representation, initialization [...] Read more.
Estimating the position and orientation of a camera with respect to an observed scene remains a fundamental problem in computer vision, particularly in calibration procedures and multi-sensor vision systems. This paper revisits the planar Perspective–n–Point (PnP) problem with emphasis on rotation representation, initialization strategy, and optimization behavior. We propose the PnP-ProCay78 algorithm, which combines analytical elimination of translation via quadratic reconstruction error with nonlinear least-squares minimization of projection residuals in Cayley parameter space. A deterministic initialization scheme based on canonical directions of the reconstruction matrix eliminates the need for spectral search over the full solution space. Experimental evaluation on heterogeneous datasets acquired from high-resolution RGB cameras and low-resolution thermal cameras demonstrates that the proposed method achieves reprojection accuracy comparable to state-of-the-art OpenCV implementations such as SQPnP and IPPE. Convergence analysis in Cayley space reveals stable and rapidly contracting optimization trajectories, with consistent behavior across sensors of significantly different resolution and noise characteristics. The results indicate that a carefully chosen rotation parameterization combined with a transparent optimization framework can yield competitive numerical performance while maintaining geometric interpretability and structural simplicity. Full article
(This article belongs to the Special Issue RGB-IR Vision for 3D Scene Analysis and Thermal Assessment)
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