PCL Developers blog

Shaohui Sun

This is my personal page

project:Change Detection: automatically determine differences between objects scanned over time.
mentor:Gordon Watson

About me

I am currently a Ph.D. candidate in Imaging Science (started from Sep. 2010) from Rochester Institute of Technology, Rochester, New York. I have various engineering backgrounds. All kinds of imaging processing techniques are interesting to me.

I work with Digital Imaging and Remote Sensing Lab at RIT. My focus is mainly on 3D building reconstruction from both LIDAR and imagery.

Click here to checkout my RIT homepage


This is an intitial estimated roadmap for this project. here. ...

Recent status updates

Introduce a joint probability distribution for estimating changes
Friday, March 30, 2012

Recently, I came across a paper in which a statistical model was proposed to detect changes between two range scans. I am going to well understand and implement it.

Currently, PCL has the capability to handle geometrical and intensity differences detection. The general criterion is the Euclidean distance. I wish to improve this by adopting the model mentioned in this paper.

I am contacting the author about the mathematical derivations in the paper and will post the progress later.

Code revision and future plan
Saturday, March 17, 2012

According to the feedback from Gordon, I revised the code I wrote. I will add more functionalities to handle RGB point cloud, as well as spatial+intensity change simultaneously.

Latest Result for Change Detection on Intensity Values
Thursday, March 08, 2012

I continue working on http://dev.pointclouds.org/issues/630.

I am still using Gordon’s data, but at this time I did more trimming and converting work. I added one more data member to pcl::SegmentDifferences which controls the threshold that the users could specify when looking at the intensity values.

By far, the new code has been working fine.






pcl::SegmentDifferences Profiling Result
Sunday, March 04, 2012

After talking with Radu, I decided to use Very Sleepy to profile the performance of pcl::SegmentDifferences. The computing time was extremely large to Trimble data. I could not wait till the program stopped before it used up the memory.

The basic statitics shows:

Filename: D:PCL_TRCSpcl_sshbinTRCS_test_debug.exe

Duration: 31549.642000s

Date: Sat Mar 03 23:29:50 2012

Samples: 3619112

I wish I could have made a figure but I haven’t found a tool to convert the result to a reasonable graph. The output .csv file was not well generated. So, here I just show the screen shot from which you could clearly see which parts are the most time consuming parts.

Add intensity differences detection to pcl::Segmentation module
Tuesday, February 28, 2012

I have opened up a new issue on http://dev.pointclouds.org/issues/630 and still working on it.