In recent years the advancement of portable consumer technology has increased at a phenomenal rate, furnishing everyone with Megapixel digital cameras and powerful mobile computing devices with Gbytes of storage capacity; GPS is now common place. In fact, technology convergence is beginning to encompass all of these elements into single affordable devices, such as the Nokia N95. The near ubiquitous ownership of digital cameras and the speed at which an image can be taken and shared with the World is promising a new paradigm in environmental observation. Every day millions of georeferenced, high oblique images are captured and shared via Internet websites such as Flickr and Panoramio, often within minutes of capture. For example, the Flickr API tells us that over half a million geo-referenced photos were taken in the Alps in 2007, of which a high proportion contain mountains viewed from many locations and aspects. There is a clear trend: geotagging photos for the sole purpose of placing one’s photos ‘on the map’, either automatically (via GPS) or manually (via GUIs), is becoming increasingly popular. It is this ever-expanding source of freely available ground-level, up-to-date, high resolution imagery and associated meta-data that the research within this paper proposes to exploit.
Spatial and temporal attractiveness analysis through geo-referenced photo alignment
Chippendale, Paul Ian;Zanin, Michele;Andreatta, Claudio
2008-01-01
Abstract
In recent years the advancement of portable consumer technology has increased at a phenomenal rate, furnishing everyone with Megapixel digital cameras and powerful mobile computing devices with Gbytes of storage capacity; GPS is now common place. In fact, technology convergence is beginning to encompass all of these elements into single affordable devices, such as the Nokia N95. The near ubiquitous ownership of digital cameras and the speed at which an image can be taken and shared with the World is promising a new paradigm in environmental observation. Every day millions of georeferenced, high oblique images are captured and shared via Internet websites such as Flickr and Panoramio, often within minutes of capture. For example, the Flickr API tells us that over half a million geo-referenced photos were taken in the Alps in 2007, of which a high proportion contain mountains viewed from many locations and aspects. There is a clear trend: geotagging photos for the sole purpose of placing one’s photos ‘on the map’, either automatically (via GPS) or manually (via GUIs), is becoming increasingly popular. It is this ever-expanding source of freely available ground-level, up-to-date, high resolution imagery and associated meta-data that the research within this paper proposes to exploit.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
