Mountain Peak Detection in Online Social Media

TL;DR

This paper introduces an automated system for classifying mountain panoramas in social media photos, estimating camera parameters, and extracting mountain peaks for applications like tagging, augmented reality, and environmental modeling.

Contribution

It presents a novel technique that estimates camera view and identifies mountain peaks from user photos, enabling new social and environmental applications.

Findings

Accurately estimates camera FOV and direction from geo-tagged photos.

Successfully extracts mountain peaks and profiles from panoramas.

Facilitates applications like peak tagging and environmental data collection.

Abstract

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).