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Camera Pose Estimation by Alignment from a Single Mountain Image

We present an alignment-based method for recovering camera position and orientation parameters from a single mountain image and digital elevation map. Camera pose estimation is achieved even without any initial position or orientation parameter estimate and requires only that the camera height above ground be known beforehand. It is also robust to partial occlusion. Using mountain peaks as features, image-model feature point alignment is hypothesized, producing a camera pose in the process. Each hypothesis is verified using mountain skyline-based geometric constraints. Combinatorial explosion is avoided using a strategy discussed in this paper. Probabilistic hypothesis generation is employed to guide the search process. Experiments involving synthetic and real images show that position accuracy compares favorably with existing algorithms.