Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W5, 401-405, 2015
https://doi.org/10.5194/isprsarchives-XL-1-W5-401-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
11 Dec 2015
3D SURFACE GENERATION FROM AERIAL THERMAL IMAGERY
B. Khodaei1, F. Samadzadegan2, F. Dadras Javan2, and H. Hasani2 1Miaad Andishe Saz, Research and Development Company, Tehran, Iran
2School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran
Keywords: Thermal Imagery, DSM, UAV, Bundle Adjustment, Dense Abstract. Aerial thermal imagery has been recently applied to quantitative analysis of several scenes. For the mapping purpose based on aerial thermal imagery, high accuracy photogrammetric process is necessary. However, due to low geometric resolution and low contrast of thermal imaging sensors, there are some challenges in precise 3D measurement of objects. In this paper the potential of thermal video in 3D surface generation is evaluated. In the pre-processing step, thermal camera is geometrically calibrated using a calibration grid based on emissivity differences between the background and the targets. Then, Digital Surface Model (DSM) generation from thermal video imagery is performed in four steps. Initially, frames are extracted from video, then tie points are generated by Scale-Invariant Feature Transform (SIFT) algorithm. Bundle adjustment is then applied and the camera position and orientation parameters are determined. Finally, multi-resolution dense image matching algorithm is used to create 3D point cloud of the scene. Potential of the proposed method is evaluated based on thermal imaging cover an industrial area. The thermal camera has 640×480 Uncooled Focal Plane Array (UFPA) sensor, equipped with a 25 mm lens which mounted in the Unmanned Aerial Vehicle (UAV). The obtained results show the comparable accuracy of 3D model generated based on thermal images with respect to DSM generated from visible images, however thermal based DSM is somehow smoother with lower level of texture. Comparing the generated DSM with the 9 measured GCPs in the area shows the Root Mean Square Error (RMSE) value is smaller than 5 decimetres in both X and Y directions and 1.6 meters for the Z direction.
Conference paper (PDF, 1255 KB)


Citation: Khodaei, B., Samadzadegan, F., Dadras Javan, F., and Hasani, H.: 3D SURFACE GENERATION FROM AERIAL THERMAL IMAGERY, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W5, 401-405, https://doi.org/10.5194/isprsarchives-XL-1-W5-401-2015, 2015.

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