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tamiwiki:projects:scanning-tami [2025/02/19 12:04] wissotskytamiwiki:projects:scanning-tami [2025/02/24 13:24] (current) wissotsky
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 <WRAP center round todo 60%> <WRAP center round todo 60%>
-Very WIP page(as of 18th February 2025), you can help by asking questions in the telegram group or in-person on Mondays+Very WIP page(as of 24th February 2025), you can help by asking questions in the telegram group or in-person on Mondays
 </WRAP> </WRAP>
  
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 After that I switched to superpoint for the feature detection and lightglue for feature matching which seems to be a fairly popular combo currently. After that I switched to superpoint for the feature detection and lightglue for feature matching which seems to be a fairly popular combo currently.
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 First I matched every frame with its 30 nearest frames(by time). First I matched every frame with its 30 nearest frames(by time).
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 I was able smooth the depth over by rasterizing the median depth(according to RaDe-GS) I was able smooth the depth over by rasterizing the median depth(according to RaDe-GS)
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 But I still had some outliers in the depth data. But I still had some outliers in the depth data.
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 I was able to fit a kernel density estimate to the depth data and then I manually found cutoff value where if the density after the global peak becomes lower it means that were past the primary peak any depth beyond that is an outlier. I was able to fit a kernel density estimate to the depth data and then I manually found cutoff value where if the density after the global peak becomes lower it means that were past the primary peak any depth beyond that is an outlier.
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 After removing the depth outliers I was able to get much cleaner results After removing the depth outliers I was able to get much cleaner results
tamiwiki/projects/scanning-tami.1739959451.txt.gz · Last modified: 2025/02/19 12:04 by wissotsky