spar 2015 - civil maps presentation by sravan puttagunta
TRANSCRIPT
SRAVAN PUTTAGUNTA
CEO, CIVIL MAPS
HTTP://CIVILMAPS.COM
A Scalable Approach to Point Cloud Processing with Deep Learning
What and who is behind Civil Maps?
$2.4 Billion $3.5 Billion $3.1 Billion
Our Office
National Energy Research Scientific Computing Center. Fastest super computer in the year 2000
Our Mission
Teach computers to make maps from 3D point cloud data.
Point Cloud Summary
A point cloud file is the output collected from a complete LiDAR system
LiDAR Sensor (laser scanning)
Inertial Measurement Unit (geo-positioning)
Hard Drive (storage of data)
Popular formats
PTS
LAS/LAZ
Point Cloud Data
Intro to Deep Learning
Deep Learning is a form of machine learning where researchers train a computer to find patterns
Thought leaders in Deep Learning
Map using Deep Learning
A B C
4 Example Feature Primitives for A
Corner detection X distribution
Y distribution
Z distribution
Z-frequency analysis
Reflectivity analysis
Spatial consistency
4 Example Feature Primitives for B
Corner detection X distribution
Y distribution
Z distribution
Z-frequency analysis
Reflectivity analysis
Spatial consistency
4 Example Feature Primitives for C
Corner detection X distribution
Y distribution
Z distribution
Z-frequency analysis
Reflectivity analysis
Spatial consistency
Train a Neural Network
1) Filter by Height
2) Filter by Reflectivity
3) Find the corners
4) Check spatial consistency
Deep Learning = Human Contextualization
Humans Computers
Querying with a Neural Network
Query w/ Neural Network Result Set
Deep Learning Demo
Mark the centerlines every 2 meters
Find all the poles
Mark the overhead electrical wires every meters
Deep Learning Demo
Manual vs. Deep Learning (X vs. Y)
Manual vs. Deep Learning (X vs. Z)
Comparative Analysis
Technology Affordability Accuracy Speed Score
Single Person 5 4 1 10
Multiple Person 1 4 1 6
Automated Software 3 2 2 7
Custom Algorithms 2 2 2 6
Deep Learning 3 5 5 13
Highest score is most feasible
The Civil Maps System (Intelligence)
• Database of 500 feature primitives
• Combinations of features 3-4 layers deep, 2 million algorithms generated per day
• Scoring algorithm • High scores survive • Low scores blacklisted
The Civil Maps System (User Interface)
Civil Maps Customers
Cloud Storage
1) Upload Point Cloud Data
2) Upload sample map for small segment
3) Deep Learning
4) Map Layers Uploaded to Visualizer
5) Report is ready for export
The Ask : Join Us
Users benefit as Civil Maps becomes smarter
High volume reduces costs for everyone
Our customers & partners have an unfair advantage
Free visualization tools
Processing fees based on number of assets per km
