Marco onderwerp onderzoek: Difference between revisions
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Two ways of guiding are the sonicguide and the navbelt. Those are both using sonic sensors to locate objects around the person. <ref>http://link.springer.com/chapter/10.1007%2F978-1-4020-6268-1_59#page-1</ref> | Two ways of guiding are the sonicguide and the navbelt. Those are both using sonic sensors to locate objects around the person. <ref name="A navigation tool for blind people" |url=http://link.springer.com/chapter/10.1007%2F978-1-4020-6268-1_59#page-1>http://link.springer.com/chapter/10.1007%2F978-1-4020-6268-1_59#page-1</ref> | ||
== | Navatar uses a camera to recognize landmarks in the surrounding area to precisely determine the position of its user. It is more precisely than gps, where gps is upto 5-10m precise, navatar can determine its location with a accuracy of 1.85m.<ref name="Navatar">http://eelke.com/navatar-indoor-navigation-blind.html</ref> | ||
Object recognition can recognize an amount of different object and also the road and or sky.<ref>http://www.engadget.com/2014/09/08/google-details-object-recognition-tech/</ref><ref>http://bryanrussell.org/projects/recognitionBySceneAlignment/index.html</ref> | |||
European obstacle recognition project for recognizing the lanes on the road for duided movement and obstacles on the road using image recognition. It is however mostly recognizing larger objects.<ref>http://cmm.ensmp.fr/~beucher/publi/eaec.pdf</ref> | |||
==notes== | |||
<references/> |
Latest revision as of 19:59, 1 September 2015
Two ways of guiding are the sonicguide and the navbelt. Those are both using sonic sensors to locate objects around the person. [1]
Navatar uses a camera to recognize landmarks in the surrounding area to precisely determine the position of its user. It is more precisely than gps, where gps is upto 5-10m precise, navatar can determine its location with a accuracy of 1.85m.[2]
Object recognition can recognize an amount of different object and also the road and or sky.[3][4]
European obstacle recognition project for recognizing the lanes on the road for duided movement and obstacles on the road using image recognition. It is however mostly recognizing larger objects.[5]