GSoC2014 Weekly report 3 - from 07-06-2014 to 3-06-2014

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GSoC2014 Weekly report 3 - from 07-06-2014 to 3-06-2014

Roberta Ravanelli

Dear all,

you can find the third weekly report at the following link:

http://opticks.org/confluence/display/~roberta.ravanelli/Weekly+report+4%3A+from+07-06-2014+to+13-06-2014


I look forward to receive your suggestions and comments.

 

Best regards,


Roberta


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Re: GSoC2014 Weekly report 3 - from 07-06-2014 to 3-06-2014

Trevor Clarke
That is a fairly typical approach to this sort of problem so I believe it will work well. You may end up needing to implement an additional filtering step before this to throw out random outliers since LIDAR can often have points that float in space (spurious reflections, etc.) and they can throw off rasterization. I'd see how it performs without this step first.

 If you need to do this, it's generally pretty easy, find the average and standard deviation of the distance values and throw out items which are far from the mean (often 3 or more standard deviations). You may also add a maximum number of points to discard (perhaps 1% or less).


On Fri, Jun 13, 2014 at 4:57 PM, Roberta Ravanelli <[hidden email]> wrote:

Dear all,

you can find the third weekly report at the following link:

http://opticks.org/confluence/display/~roberta.ravanelli/Weekly+report+4%3A+from+07-06-2014+to+13-06-2014


I look forward to receive your suggestions and comments.

 

Best regards,


Roberta


------------------------------------------------------------------------------
HPCC Systems Open Source Big Data Platform from LexisNexis Risk Solutions
Find What Matters Most in Your Big Data with HPCC Systems
Open Source. Fast. Scalable. Simple. Ideal for Dirty Data.
Leverages Graph Analysis for Fast Processing & Easy Data Exploration
http://p.sf.net/sfu/hpccsystems
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--
Trevor R.H. Clarke
Computer Science House
Rochester Institute of Technology
[hidden email]
http://www.csh.rit.edu/~retrev/

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HPCC Systems Open Source Big Data Platform from LexisNexis Risk Solutions
Find What Matters Most in Your Big Data with HPCC Systems
Open Source. Fast. Scalable. Simple. Ideal for Dirty Data.
Leverages Graph Analysis for Fast Processing & Easy Data Exploration
http://p.sf.net/sfu/hpccsystems
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