Nicolau L. Werneck has had a career focused on computer science and engineering. He graduated with a degree in electrical engineering and worked on signal processing and pattern recognition problems. He then earned a master's degree researching electric guitar physics. Werneck completed a PhD studying computer vision applied to mobile robotics. His research focused on monocular vision techniques to build 3D models of environments. Werneck has worked at Google and a startup applying his skills and continues researching monocular vision methods.

1. Professional experience presentation
Nicolau L. Werneck, PhD
São Paulo, Brazil
19 November 2013

2. Personal background
Always loved computers, started coding before
college.
Interest in science and arts in general, including
music, photography and cinema.
Predisposition to academic life, doing research and
interdisciplinarity.
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3. Graduation
Graduated in Electrical Engineering at UFMG, with
emphasis on computation.
Favorite subjects: signal processing, optimization.
Worked at the CEFALA lab, studied many signal
processing and pattern recognition problems.
→ Recognition and synthesis of face, speech and musical
instruments; Fingerprint recognition; Visual tracking.
→ Concern for building physical and probabilistic models
of the studied phenomena.
Internship at a biotech start-up, applying statistical
pattern recognition to genetic data from bovines.
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4. Masters
Masters in Electrical Engineering at UNICAMP.
Continued undergrad research on electric guitars.
Physics of vibrating strings, electronic distortions
and timbre perception.
Conducted several experiments:
→ Detection of non-linear effects in string vibration.
→ Parameter estimation of electronic circuits.
→ Sensibility of distortion perception.
Favorite subjects: ML, Cog. Sci, Computer Vision.
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5. Doctorate
Worked at the LTI, USP, supervised by Prof. Anna
Helena Reali Costa.
→ Lab topics: computer vision, mobile robots, task
planning, RL, POMDPs, policy reuse, MAS.
Eventually started working with Computer Vision
applied to Mobile Robotics.
“Disenchanted” with stereo rigs and with methods
based on point or line extraction.
Started studying edgel-based monocular vision,
hoping to build solid models of environments.
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6. Research Motivations
Create environment models more suitable for
robotics, withs solids and “meaning”.
Explore the “Manhattan world” assumption.
Monocular operation and good computational
performance. Be able to run on a smartphone.
To handle distorted and omnidirectional images.
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7. Research Focus
Research started with simpler problems, assuming
rectilinear motion and 2D models. [1, 2, 3]
We noticed rotation is a great nuisance for mapping, but
“Manhattan world”
Decouple orientation &
Line-based
+
→
assumption
position estimation.
vision
So we started to study orientation estimation.
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8. Research Proposal
Corisco is an edgel-based orientation-estimation method.
It minimizes an objective function defined with
M-estimation, using RANSAC and FilterSQP. [4, 5]
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9. Research Results
Corisco was implemented in Python and C, and is
available at http://github.com/nlw0/corisco.
Compared to Snavely et al. 2006, Denis et al. 2008 and
other methods.
Future work: SLAM and calibration.
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10. Google work
Google uses scanners that take pictures of open
books. A solid model is necessary for dewarping.
They wanted a new algorithm to be used in an
open-source “lightweight” book scanner.
I proposed a square mesh model, and to impose
inextensibility by using constrained optimization.
Implemented just a very simple prototype. Today
I’m working on a purely monocular method.
This work led me to study FilterSQP, used in Corisco.
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11. Geekie work
The company uses Item Response Theory (IRT) to
evaluate the performance of students.
I implemented a better parameter estimation
algorithm for the IRT analyses.
The current code has already been used to analyze
100k tests.
Currently working on an information system for
research and analytics tasks. (Kaiju framework.)
Other activities: BIB design solver, analytics.
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12. Future plans
Get back at working with computer vision.
Contribute to creating great CV tools and products
for the industry and academy.
Research ambitions: monocular vision method to
create solid environemnt models.
Thank you!
Nicolau Werneck <nwerneck@gmail.com>
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13. Corisco Examples
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14. Corisco Examples
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15. Corisco Examples
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16. Corisco Examples
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17. Corisco Examples
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18. Corisco Examples
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19. Corisco Examples
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20. Corisco Examples
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21. Referências Bibliográficas
[1] Nicolau Leal Werneck, Flávio Sales Truzzi, and Anna Helena Reali
Costa. Medição de distância e altura de bordas horizontais com visão
monocular linear para robôs móveis. In Workshop de Visão
Computacional, São Paulo, SP, Brasil, 2009. Universidade Presbiteriana
Mackenzie. URL http://nwerneck.sdf.org/almoxarifado/59760_
WerneckTruzziCosta.pdf.
[2] Nicolau Leal Werneck and Anna Helena Reali Costa. Monocular visual
mapping with the Fast Hough Transform. In Workshop de Visão
Computacional, Presidente Prudente, SP, Brasil, 2010. FTC-UNESP.
URL http://iris.sel.eesc.usp.br/wvc/anais_WVC2010/artigos/
oral/72827.pdf.
[3] Nicolau Leal Werneck and Anna Helena Reali Costa. Mapping with
monocular vision in two dimensions. International Journal of Natural
Computing Research, 1(4):56–65, 2010. URL
http://nwerneck.sdf.org/almoxarifado/WerneckCosta10.pdf.
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22. [4] Nicolau Leal Werneck and Anna Helena Reali Costa. Speeding up
probabilistic inference of camera orientation by function approximation
and grid masking. In Gladimir Baranoski and Vaclav Skala, editors,
WSCG 2011 Communication Papers, pages 127–134, Plzen, Czech
Republic, 2011. UNION Agency. URL
http://nwerneck.sdf.org/almoxarifado/nic-wscg2011.pdf.
[5] Nicolau Leal Werneck and Anna Helena Reali Costa. Corisco: Robust
edgel-based orientation estimation for generic camera models. Image
and Vision Computing, 2013? Accepted, final version in preparation.
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