Mountain Peak Detection in Online Social Media
This addresses the need for automated mountain peak identification in social media for applications in tagging and environmental modeling, but it is incremental as it builds on existing image processing techniques.
The paper tackles the problem of automatically detecting and extracting mountain peaks from geo-tagged photographs using a matching algorithm on edge maps and rendered silhouettes, enabling applications like peak tagging and augmented reality.
We present a system for the classification of mountain panoramas from user-generated photographs followed by identification and extraction of mountain peaks from those panoramas. We have developed an automatic technique that, given as input a geo-tagged photograph, estimates its FOV (Field Of View) and the direction of the camera using a matching algorithm on the photograph edge maps and a rendered view of the mountain silhouettes that should be seen from the observer's point of view. The extraction algorithm then identifies the mountain peaks present in the photograph and their profiles. We discuss possible applications in social fields such as photograph peak tagging on social portals, augmented reality on mobile devices when viewing a mountain panorama, and generation of collective intelligence systems (such as environmental models) from massive social media collections (e.g. snow water availability maps based on mountain peak states extracted from photograph hosting services).