”Photogrammetry is the art, science and technology of obtaining reliable information about physical objects and the environment through the process of recording, measuring, and interpreting photographic images and patterns of electromagnetic radiant energy and other phenomena” (Mc Glone, 2004).
Photogrammetry is a very accurate and reliable post-processing mapping method, which needs calibrated high quality cameras, and strict methodologies to calculate 3D points (and derivatives) in space.
Since photogrammetry is almost as old as photography itself, is still confined in laborious and tedious tasks, as well as mere stereo extraction of points.
By taking advantage of modern computer vision algorithms and techniques, one can overcome aforementioned limitations towards more robust and automated 3D modelling or mapping applications.
So, one can say that "Photogrammetric vision is the fusion of photogrammetry and computer vision to support fully automated 3D modelling and mapping tasks, through the recordings of visual & electromangetic sensors" , or if you wish, the vision of the future of photogrammetry.
Lab's brochure (2013)
"Machine vision is the analysis of images to extract data for controlling a process or activity." (Christopher, 2004).
Machine vision is the application of computer vision to industry and manufacturing. Whereas computer vision is the general discipline of making computers see (understand what is perceived visually), machine vision, being an engineering discipline, is interested in digital input/output. (wikipedia, 2011)
Real time application that in most cases uses apriori knowledge to reliably automate tasks.
"Simultaneous localization and mapping (SLAM) is a technique used by robots and autonomous vehicles to build up a map within an unknown environment (without a priori knowledge), or to update a map within a known environment (with a priori knowledge from a given map), while at the same time keeping track of their current location." (wikipedia, 2011)
Less accurate, but real time application that combines mapping and localization.
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Last Update of site content: 29.06.2018