Automatic Photo-to-Terrain Alignment for the Annotation of Mountain Pictures

Lionel Baboud,
Martin Čadík,
Elmar Eisemann,
Hans-Peter Seidel,


We present a system for the annotation and augmentation of mountain photographs. The key issue resides in the registration of a given photograph with a 3D geo-referenced terrain model. Typical outdoor images contain little structural information, particularly mountain scenes whose aspect changes drastically across seasons and varying weather conditions. Existing approaches usually fail on such difficult scenarios. To avoid the burden of manual registration, we propose a novel automatic technique. Given only a viewpoint and FOV estimates, the technique is able to automatically derive the pose of the camera relative to the geometric terrain model. We make use of silhouette edges, which are one of the most reliable features that can be detected in the targeted situations. Using an edge detection algorithm, our technique then searches for the best match with silhouette edges rendered with the synthetic model. We develop a robust matching metric allowing us to cope with noise inevitably present among detected edges (e.g. due to clouds, snow, rocks, forests, or any phenomenon not encoded in the digital model). Once registered against the model, photographs can easily be augmented with annotations (e.g. topographic data, peak names, paths), which would otherwise imply a tedious fusion process. We further illustrate various other applications, such as 3D model-assisted image enhancement, or, inversely, texturing of digital models.


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