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Mathias Perrollaz
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2010 – 2019
- 2014
- [j5]Mathias Perrollaz, Raphaël Labayrade
, Dominique Gruyer, Alain Lambert, Didier Aubert:
Proposition of Generic Validation criteria using Stereo-Vision for on-Road obstacle Detection. Int. J. Robotics Autom. 29(1) (2014) - [j4]Qadeer Baig, Mathias Perrollaz, Christian Laugier:
A Robust Motion Detection Technique for Dynamic Environment Monitoring: A Framework for Grid-Based Monitoring of the Dynamic Environment. IEEE Robotics Autom. Mag. 21(1): 40-48 (2014) - [c14]Lukas Rummelhard, Amaury Nègre, Mathias Perrollaz, Christian Laugier:
Probabilistic Grid-Based Collision Risk Prediction for Driving Application. ISER 2014: 821-834 - 2013
- [j3]Alexandros Makris, Mathias Perrollaz, Christian Laugier:
Probabilistic Integration of Intensity and Depth Information for Part-Based Vehicle Detection. IEEE Trans. Intell. Transp. Syst. 14(4): 1896-1906 (2013) - [c13]Puneet Kumar, Mathias Perrollaz, Stéphanie Lefevre, Christian Laugier:
Learning-based approach for online lane change intention prediction. Intelligent Vehicles Symposium 2013: 797-802 - 2012
- [j2]Mathias Perrollaz, John-David Yoder, Amaury Nègre, Anne Spalanzani, Christian Laugier:
A Visibility-Based Approach for Occupancy Grid Computation in Disparity Space. IEEE Trans. Intell. Transp. Syst. 13(3): 1383-1393 (2012) - [c12]Qadeer Baig, Mathias Perrollaz, Jander Botelho Do Nascimento, Christian Laugier:
Using fast classification of static and dynamic environment for improving Bayesian occupancy filter (BOF) and tracking. ICARCV 2012: 656-661 - [c11]Mathias Perrollaz, Sami Khorbotly, Amber Cool, John-David Yoder, Eric T. Baumgartner
Teachless teach-repeat: Toward vision-based programming of industrial robots. ICRA 2012: 409-414 - [c10]Juan David Adarve
Computing occupancy grids from multiple sensors using linear opinion pools. ICRA 2012: 4074-4079 - [c9]John-David Yoder, Jeffrey West, Eric T. Baumgartner, Mathias Perrollaz, Michael J. Seelinger, Matthew L. Robinson:
Experiments Comparing Precision of Stereo-Vision Approaches for Control of an Industrial Manipulator. ISER 2012: 245-256 - 2011
- [j1]Christian Laugier, Igor E. Paromtchik, Mathias Perrollaz, Yong Mao, John-David Yoder, Christopher Tay, Kamel Mekhnacha, Amaury Nègre:
Probabilistic Analysis of Dynamic Scenes and Collision Risks Assessment to Improve Driving Safety. IEEE Intell. Transp. Syst. Mag. 3(4): 4-19 (2011) - [c8]Igor E. Paromtchik, Mathias Perrollaz, Christian Laugier:
Fusion of telemetric and visual data from road scenes with a lexus experimental platform. Intelligent Vehicles Symposium 2011: 746-751 - 2010
- [c7]Igor E. Paromtchik, Christian Laugier, Mathias Perrollaz, Yong Mao, Amaury Nègre, Christopher Tay:
The ArosDyn project: Robust analysis of dynamic scenes. ICARCV 2010: 1403-1409 - [c6]Mathias Perrollaz, John-David Yoder, Anne Spalanzani, Christian Laugier:
Using the disparity space to compute occupancy grids from stereo-vision. IROS 2010: 2721-2726 - [c5]John-David Yoder, Mathias Perrollaz, Igor E. Paromtchik, Yong Mao, Christian Laugier:
Experiments in Vision-Laser Fusion Using the Bayesian Occupancy Filter. ISER 2010: 899-907 - [c4]Mathias Perrollaz, John-David Yoder, Christian Laugier:
Using obstacles and road pixels in the disparity-space computation of stereo-vision based occupancy grids. ITSC 2010: 1147-1152 - [c3]Mathias Perrollaz, Anne Spalanzani, Didier Aubert:
Probabilistic representation of the uncertainty of stereo-vision and application to obstacle detection. Intelligent Vehicles Symposium 2010: 313-318
2000 – 2009
- 2008
- [b1]Mathias Perrollaz:
Détection d'obstacles multi-capteurs supervisée par stéréovision. (Multi-sensor road obstacle deetection controled by stereovision). Pierre and Marie Curie University, Paris, France, 2008 - 2007
- [c2]Mathias Perrollaz, Raphaël Labayrade, Romain Gallen, Didier Aubert:
A Three Resolution Framework for Reliable Road Obstacle Detection Using Stereovision. MVA 2007: 469-472 - 2006
- [c1]Nicolas Hautière
Road Scene Analysis by Stereovision: a Robust and Quasi-Dense Approach. ICARCV 2006: 1-6
Coauthor Index
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