Difference between revisions of "Mathieu Labbe"

From IntRoLab
(Mathieu Labbé, M.Sc.A.)
Line 86: Line 86:
 
* [[Image:Find_object.png|link=http://find-object.googlecode.com|48px|Find-Object]] Object detection using SURF/SIFT like features.
 
* [[Image:Find_object.png|link=http://find-object.googlecode.com|48px|Find-Object]] Object detection using SURF/SIFT like features.
 
* [http://utilite.googlecode.com UtiLite] C++ utilities.
 
* [http://utilite.googlecode.com UtiLite] C++ utilities.
* [http://code.google.com/p/fovis-pkg/ FOVIS ros-pkg] ROS Wrapper of the Fovis library: a visual odometry approach using Kinect-like sensors.
 
 
* [http://code.google.com/p/vvindow/ VVindow] A virtual window project: Head tracking using a Kinect for Virtual Reality.
 
* [http://code.google.com/p/vvindow/ VVindow] A virtual window project: Head tracking using a Kinect for Virtual Reality.
 
* [http://code.google.com/p/semolearning/ SeMoLearning] Graph-based Bayesian Sensorimotor Learning.
 
* [http://code.google.com/p/semolearning/ SeMoLearning] Graph-based Bayesian Sensorimotor Learning.
Line 95: Line 94:
 
* [[Image:Find_object.png|link=http://find-object.googlecode.com|48px|Find-Object]] Object detection using SURF/SIFT like features.
 
* [[Image:Find_object.png|link=http://find-object.googlecode.com|48px|Find-Object]] Object detection using SURF/SIFT like features.
 
* [http://utilite.googlecode.com UtiLite] C++ utilities.
 
* [http://utilite.googlecode.com UtiLite] C++ utilities.
* [http://code.google.com/p/fovis-pkg/ FOVIS ros-pkg] ROS Wrapper of the Fovis library: a visual odometry approach using Kinect-like sensors.
 
 
* [http://code.google.com/p/vvindow/ VVindow] A virtual window project: Head tracking using a Kinect for Virtual Reality.
 
* [http://code.google.com/p/vvindow/ VVindow] A virtual window project: Head tracking using a Kinect for Virtual Reality.
 
* [http://code.google.com/p/semolearning/ SeMoLearning] Graph-based Bayesian Sensorimotor Learning.
 
* [http://code.google.com/p/semolearning/ SeMoLearning] Graph-based Bayesian Sensorimotor Learning.

Revision as of 18:26, 8 June 2015

Mathieu Labbé, M.Sc.A.

MathieuLabbé.jpg Contact information :
  • IntRoLab laboratory, Interdisciplinary Institute of Technological Innovation (3IT), Université de Sherbrooke
  • Email : mathieu.m.labbe (at) usherbrooke.ca


Scholarship[edit]

  • 2011-201x Ph. D. in electrical engineering, Université de Sherbrooke
  • 2009-2010 Master of electrical engineering, Université de Sherbrooke
  • 2004-2008 Bachelor of computer engineering, Université de Sherbrooke


Honors and Awards[edit]


Interests[edit]

  • Mobile robotic
  • Simultaneous Localization And Mapping (SLAM)
  • Real-time systems
  • Autonomous learning



Open source softwares[edit]

  • RTAB-Map Loop closure detection for Simultaneous Localization and Mapping (SLAM).
  • Find-Object Object detection using SURF/SIFT like features.
  • UtiLite C++ utilities.
  • VVindow A virtual window project: Head tracking using a Kinect for Virtual Reality.
  • SeMoLearning Graph-based Bayesian Sensorimotor Learning.


Papers[edit]

  • M. Labbé and F. Michaud, “Online Global Loop Closure Detection for Large-Scale Multi-Session Graph-Based SLAM,” in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2014. (pdf) (IEEE Xplore)
  • M. Labbé and F. Michaud, “Appearance-Based Loop Closure Detection for Online Large-Scale and Long-Term Operation,” in IEEE Transactions on Robotics, vol. 29, no. 3, pp. 734-745, 2013. (pdf) (IEEE Xplore)
  • M. Labbé and F. Michaud, “Memory management for real-time appearance-based loop closure detection,” in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2011, pp. 1271–1276. (pdf) (IEEE Xplore)