gerald dalley signal analysis and machine perception laboratory the ohio state university 07 feb...
TRANSCRIPT
![Page 1: Gerald Dalley Signal Analysis and Machine Perception Laboratory The Ohio State University 07 Feb 2002 Linux Clustering Software + Surface Reconstruction](https://reader035.vdocuments.mx/reader035/viewer/2022062804/56649e225503460f94b0f550/html5/thumbnails/1.jpg)
Gerald DalleySignal Analysis and Machine Perception Laboratory
The Ohio State University
07 Feb 2002
Linux Clustering SoftwareLinux Clustering Software++
Surface Reconstruction Surface Reconstruction from Point Clouds from Point Clouds
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Topic MotivationTopic Motivation
• Computationally intensive work
• Many “small” execution jobs at each phase
Range Image Aquisition
Initial Detection(“Pop-out”)
Ballooning
Surface Reconstruction
Surface Segmentation
Recognition
Multiple balloons
must be merged:
• Segmentation requires dense meshes
• Non-sparse balloons are “leaky”
• Merging overlapping balloons is non-trivial
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OutlineOutline
• Part 1: Linux Clustering Software– ClusterIt– Portable Batch System
• Part 2: Surface Reconstruction– Preliminaries– Curve Reconstruction– Cocone Algorithm– Undersampling– Some Results
• Current Status• Further Reading
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Cluster Software:Cluster Software:
ClusterItClusterIt
• What is it?– Simultaneous execution on a set of Linux boxes– Execution on “any” Linux box
(but PBS is much better)
• What do I have to do to use it?– See http://sampl.eng.ohio-state.edu/~dalleyg/faq/index.html for
instructions on configuring SSH
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Cluster Software:Cluster Software:
SAMPL Cluster GroupsSAMPL Cluster Groups
See /etc/dsh.cluster on a Linux box for the full set of groups
Group Comments
a All processors (use with jsd, etc.)
a1 All boxes (use with dsh, etc.)
b All Beowulf processors
b1 All Beowulf boxes
m All of the Micron boxes
dc All processors on the dual Celerons
dc1 All dual Celeron boxes
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Cluster Software:Cluster Software:
dshdsh• When would I use it?
– Same command, many machines– Batch job preparation– Administrative work
• Usage– dsh -g om 'hostname -i'
– Resultssampl01: 164.107.162.9 sampl02: 164.107.162.10 sampl10: 164.107.162.18 sampl12: 164.107.162.20
Group (required!) Remote command (quoted)
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Cluster Software:Cluster Software:
dsh Examplesdsh Examples
• Good examples– dsh -g om 'hostname -i'– dsh –g om 'hostname > /tmp/tmpfile'– dsh –g a1 'smbmount //samplf04/dalleyg /u/dalleyg -o umask=077,dmask=077, password=PASSWORD'
• What to be careful about– Using quotes (single or double)– Redirecting input or output
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Cluster Software:Cluster Software:
Other ClusterIt ExamplesOther ClusterIt Examples• pcp -g a1 datafile /tmp/datafile
– Copies file datafile from the current directory to /tmp/datafile on all machines in the a1 group
– Useful for copying files to local temporary storage
• prm -g a1 /tmp/datafile– Deletes /tmp/datafile on all machines in the a1
group
– Useful for cleanup of local temporary storage, etc.
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Cluster Software:Cluster Software:
Portable Batch SystemPortable Batch System
• What is it?– Manages submission and execution of large
batch jobs– Allows balancing between users– Used for single multi-processor machines all
the way up to compute farms with many Crays (e.g. OSC)
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Cluster Software:Cluster Software:
Portable Batch System Portable Batch System (cont’d.)(cont’d.)
• Submitting a job (from eepc359 only)*– qsub -N jobname jobprogram– qsub -N Test /home/dalleyg/nfs/test2.pl
• Cluster status– qstat -f -B
• xpbs– Helps you create job scripts, configure advanced options, etc.
• xpbsmon– Helps you monitor the state of the machines on the cluster
*The configuration is still being debugged.
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Part 2: Part 2:
Surface Reconstruction…Surface Reconstruction…
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Surface Reconstruction Preliminaries: Surface Reconstruction Preliminaries:
Voronoi DiagramsVoronoi Diagrams• Voronoi Cell of x
– The set of points that are closer to x than to any other sample point
Voronoi cell
Voronoi edge
Voronoi vertex
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Surface Reconstruction Preliminaries:Surface Reconstruction Preliminaries:
Preliminaries: Medial AxisPreliminaries: Medial Axis
• Medial Axis: – Find all circles
that tangentially touch the curve in at least 2 points
– Medial axis = centers of all those circles
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Surface Reconstruction Preliminaries: Surface Reconstruction Preliminaries:
ε-samplingε-samplingf(x) ≡ feature size at point x
= distance to the medial axis at point x
Sampling criterion: each sample point x is at most εf(x) from the next closest sample (0 < ε < 1, typically).
Important note: When ε is small, the curve locally looks flat
f(x)
x
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Surface Reconstruction:Surface Reconstruction:
Curve ReconstructionCurve Reconstruction• Algorithm:
– Find the closest point, p, to x and connect them
– Find the closest point, q, to x such that the angle pxq is at least 90°.
• Guaranteed to work when ε ≤ ⅓
x
p
q
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Surface Reconstruction:Surface Reconstruction:
Cocone AlgorithmCocone Algorithm
• p+ ≡ pole of p = point in the Voronoi cell farthest from p
• ε < 0.1 → – the vector from p to p+ is
within π/8 of the true surface normal
– The surface is nearly flat within the cell Voronoi cell of p
p+
p
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Sample Reconstructed SurfacesSample Reconstructed Surfaces
Foot images from Prof. Dey
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TuT StatusTuT StatusRange Image
Aquisition
Initial Detection(“Pop-out”)
Ballooning
Surface Reconstruction
Surface Segmentation
Recognition
Software written
See Kanu
Software written (by Kanu), generating data
Software written (by Prof. Dey)
Evaluating several variants
To be done
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Further ReadingFurther Reading
– Clusterit• http://www.garbled.net/clusterit.html• http://sampl.eng.ohio-state.edu/~dalleyg/faq/index.html
– Portable Batch System• http://www.openpbs.org
– Official web site (ask if you need the password)
• http://www-itg.lbl.gov/Grid/public/pbs/pbs.v2.3_admin.pdf– Detailed administration/usage guide
• http://www-math.cudenver.edu/~jmandel/mri/Schedulers-overview.pdf– Slideshow introduction to PBS by Doug Johnson from the Ohio Supercomputer Center
– Surface Reconstruction• http://www.cis.ohio-state.edu/~tamaldey/• N. Amenta, S. Choi, T. K. Dey and N. Leekha. A simple algorithm for homeomorphic
surface reconstruction. Proc. 16th ACM Symposium on Computational Geometry, 2000, 213--222.