Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1, 149-154, 2014
https://doi.org/10.5194/isprsarchives-XL-1-149-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
07 Nov 2014
Linear Approach for Initial Recovery of the Exterior Orientation Parameters of Randomly Captured Images by Low-Cost Mobile Mapping Systems
F. He and A. Habib Lyles School of Civil Engineering, Purdue University, 47906, West Lafayette, Indiana, USA
Keywords: Exterior Orientation, Relative Orientation, Linear Approaches, Bundle Adjustment Abstract. In this paper, we present a novel linear approach for the initial recovery of the exterior orientation parameters (EOPs) of images. Similar to the conventional Structure from Motion (SfM) algorithm, the proposed approach is based on a two-step strategy. In the first step, the relative orientation of all possible image stereo-pairs is estimated. In the second step, a local coordinate frame is established, and an incremental image augmentation process is implemented to reference all the remaining images into a local coordinate frame. Since our approach is based on a linear solution for both the relative orientation estimation as well as the initial recovery of the image EOPs, it does not require any initial approximation for the optimization process. Another advantage of our approach is that it does not require any prior knowledge regarding the sequence of the image collection procedure, therefore, it can handle a set of randomly collected images in the absence of GNSS/INS information. In order to illustrate the feasibility of our approach, several experimental tests are conducted on real datasets captured in either a block or linear trajectory configuration. The results demonstrate that the initial image EOPs obtained are accurate and can serve as a good initialization for an additional bundle adjustment process.
Conference paper (PDF, 575 KB)


Citation: He, F. and Habib, A.: Linear Approach for Initial Recovery of the Exterior Orientation Parameters of Randomly Captured Images by Low-Cost Mobile Mapping Systems, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1, 149-154, https://doi.org/10.5194/isprsarchives-XL-1-149-2014, 2014.

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