Feel free to ask me for an updated CV
Research Interest
I am an Industrial PhD student working on research and innovation project with the SNCF to inspect the railway network using 3D computer vision and pattern recognition techniques.
My research interests are in 3D reconstruction (Rigid and deformable, Stereovision, 3D structured lightning, Shape from X, Structure from Motion etc.), Image processing, Optical Calibration (Convention and Non-convention optics), Sensor Fusion (2D, 2.5D, 3D).
Experience Application
Real-time, Precise measurement(Metrology), Quality Control, Medical, Oil and gas, Robotics, Surveillance and Security etc
Recently
I am currently investigating deep fusion under convolution neural network for Autonomous driving
PhD Thesis
Multi-view analysis for 3D industrial inspection (Metrology)
CONFIDENTIAL
eter O. Fasogbon,
Industrial PhD. Student (R&D Project)
University
CRISTAL Laboratory of Lille1 University,
UMR, National Center for Scientific Research (CNRS) 9198,
Cité Scientifique, Bat. P2,
59655 Villeneuve d'Ascq Cedex, France
Industry
SNCF Réseau (French National Railway Company),
Direction Engineering and Projects, Electricity Department,
CES3 - R&D, Simulations, Expertises and Measures,
6, avenue François Mitterand,
93574 La Plaine Saint Denis Cedex, France
Email: peter.fasogbon89-at-gmail.com
Contact: +33.6.15.80.64.74 (mobile)
Master Thesis
Real-time segmentation for minimal invasive surgery (Laparoscopy)
Segmentation is the first step in our Monocular 3D reconstruction framework used for computer assisted laparoscopy. The used surgical instruments introduce artifacts in the reconstructed 3D, therefore we need to segment them out.
Also, the segmentation task needs to be done at a very short time so that, "less segmentation and 3D reconstruction time" ensures we have a 3D reconstruction framework that can be use in real-time by the surgeons.