<html xmlns:o="urn:schemas-microsoft-com:office:office" xmlns:w="urn:schemas-microsoft-com:office:word" xmlns:m="http://schemas.microsoft.com/office/2004/12/omml" xmlns="http://www.w3.org/TR/REC-html40"><head><meta http-equiv=Content-Type content="text/html; charset=utf-8"><meta name=Generator content="Microsoft Word 15 (filtered medium)"><style><!--
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--></style></head><body lang=EN-US link=blue vlink="#954F72" style='word-wrap:break-word'><div class=WordSection1><p class=MsoNormal>First a result, then its metadata, then the sampling and contextualization with other data and metadata for a new result, then the interpretation as metadata for the new resolution.</p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal><o:p> </o:p></p><div style='mso-element:para-border-div;border:none;border-top:solid #E1E1E1 1.0pt;padding:3.0pt 0in 0in 0in'><p class=MsoNormal style='border:none;padding:0in'><b>From: </b><a href="mailto:brutzman@nps.edu">Don Brutzman</a><br><b>Sent: </b>Wednesday, April 28, 2021 2:17 PM<br><b>To: </b><a href="mailto:joedwil@earthlink.net">Joseph D Williams</a>; <a href="mailto:yottzumm@gmail.com">John Carlson</a><br><b>Cc: </b><a href="mailto:x3d-public@web3d.org">X3D Graphics public mailing list</a><br><b>Subject: </b>Re: [x3d-public] Computer Graphics "truth" data for learning vision.</p></div><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>hmmm if we add metadata to characterize relationships between these inverses, maybe we can remember what we said about them too...</p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>On 4/24/2021 10:41 AM, Joseph D Williams wrote:</p><p class=MsoNormal>> * So computer graphics takes geometry/shapes and produces video.</p><p class=MsoNormal>> * Computer vision takes videos and produces geometry/shapes.</p><p class=MsoNormal>> </p><p class=MsoNormal>> All that is needed is the common context and ontology to transcode between the representations.</p><p class=MsoNormal>> </p><p class=MsoNormal>> Figure out the style sheet, maybe as you go, then see what might appear from the media you sample and what might manifest in the space you are building.</p><p class=MsoNormal>> </p><p class=MsoNormal>> *From: *John Carlson <mailto:yottzumm@gmail.com></p><p class=MsoNormal>> *Sent: *Friday, April 23, 2021 9:15 PM</p><p class=MsoNormal>> *To: *X3D Graphics public mailing list <mailto:x3d-public@web3d.org></p><p class=MsoNormal>> *Subject: *[x3d-public] Computer Graphics "truth" data for learning vision.</p><p class=MsoNormal>> </p><p class=MsoNormal>> So computer graphics takes geometry/shapes and produces video.</p><p class=MsoNormal>> </p><p class=MsoNormal>> Computer vision takes videos and produces geometry/shapes.</p><p class=MsoNormal>> </p><p class=MsoNormal>> Can we take the computer graphics input and output data and help out the</p><p class=MsoNormal>> </p><p class=MsoNormal>> computer vision people?</p><p class=MsoNormal>> </p><p class=MsoNormal>> That is, output data from computer graphics is input to computer vision,</p><p class=MsoNormal>> </p><p class=MsoNormal>> and the neural network is trained to produce computer graphics input data.</p><p class=MsoNormal>> </p><p class=MsoNormal>> Google: geoffrey hinton GLOM</p><p class=MsoNormal>> </p><p class=MsoNormal>> John</p><p class=MsoNormal>> </p><p class=MsoNormal>> _______________________________________________</p><p class=MsoNormal>> </p><p class=MsoNormal>> x3d-public mailing list</p><p class=MsoNormal>> </p><p class=MsoNormal>> x3d-public@web3d.org</p><p class=MsoNormal>> </p><p class=MsoNormal>> http://web3d.org/mailman/listinfo/x3d-public_web3d.org</p><p class=MsoNormal>> </p><p class=MsoNormal>> </p><p class=MsoNormal>> _______________________________________________</p><p class=MsoNormal>> x3d-public mailing list</p><p class=MsoNormal>> x3d-public@web3d.org</p><p class=MsoNormal>> http://web3d.org/mailman/listinfo/x3d-public_web3d.org</p><p class=MsoNormal>> </p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>all the best, Don</p><p class=MsoNormal>-- </p><p class=MsoNormal>Don Brutzman Naval Postgraduate School, Code USW/Br brutzman@nps.edu</p><p class=MsoNormal>Watkins 270, MOVES Institute, Monterey CA 93943-5000 USA +1.831.656.2149</p><p class=MsoNormal>X3D graphics, virtual worlds, navy robotics http://faculty.nps.edu/brutzman</p><p class=MsoNormal><o:p> </o:p></p></div></body></html>