Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B3, 39-42, 2016
https://doi.org/10.5194/isprs-archives-XLI-B3-39-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
09 Jun 2016
ORIENTATION MODELING FOR AMATEUR CAMERAS BY MATCHING IMAGE LINE FEATURES AND BUILDING VECTOR DATA
C. H. Hung1, W. C. Chang1, and L. C. Chen2 1Dept. of Civil Engineering , National Central University, Taiwan
2Center for Space and Remote Sensing Research, National Central University, Taiwan
Keywords: Direct Georeferencing, Feature Line Matching, Line Control, Orientation Modeling, Orientation Parameters Abstract. With the popularity of geospatial applications, database updating is getting important due to the environmental changes over time. Imagery provides a lower cost and efficient way to update the database. Three dimensional objects can be measured by space intersection using conjugate image points and orientation parameters of cameras. However, precise orientation parameters of light amateur cameras are not always available due to their costliness and heaviness of precision GPS and IMU. To automatize data updating, the correspondence of object vector data and image may be built to improve the accuracy of direct georeferencing. This study contains four major parts, (1) back-projection of object vector data, (2) extraction of image feature lines, (3) object-image feature line matching, and (4) line-based orientation modeling. In order to construct the correspondence of features between an image and a building model, the building vector features were back-projected onto the image using the initial camera orientation from GPS and IMU. Image line features were extracted from the imagery. Afterwards, the matching procedure was done by assessing the similarity between the extracted image features and the back-projected ones. Then, the fourth part utilized line features in orientation modeling. The line-based orientation modeling was performed by the integration of line parametric equations into collinearity condition equations. The experiment data included images with 0.06 m resolution acquired by Canon EOS Mark 5D II camera on a Microdrones MD4-1000 UAV. Experimental results indicate that 2.1 pixel accuracy may be reached, which is equivalent to 0.12 m in the object space.
Conference paper (PDF, 1003 KB)


Citation: Hung, C. H., Chang, W. C., and Chen, L. C.: ORIENTATION MODELING FOR AMATEUR CAMERAS BY MATCHING IMAGE LINE FEATURES AND BUILDING VECTOR DATA, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B3, 39-42, https://doi.org/10.5194/isprs-archives-XLI-B3-39-2016, 2016.

BibTeX EndNote Reference Manager XML