Difference between revisions of "3D Structure From Visual Motion"
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| + | Recent news you should be aware of ... | ||
| + | * New schedule published with teachers specified | ||
| + | * The schedule of 2014 lectures is out! | ||
| + | * A new version of the course is scheduled for the year 2013/2014 | ||
| + | |||
| + | <!-- | ||
| + | * 17/05/2012: Change in the lecture topics in the schedule | ||
| + | * 18/04/2012: Change of Fri 20/04 room: lecture will be in D2.2 | ||
| + | * 11/04/2012: Rooms for classes updated and first class material published. | ||
| + | * 18/03/2012: Detailed course schedule published! | ||
| + | * 06/03/2012: Detailed course schedule coming out soon if you did not received the notification email please contact me! | ||
| + | --> | ||
| + | |||
| + | This is a description page for the PhD course on ''3D Structure from Visual Motion: Novel Techniques in Computer Vision and Autonomous Robots/Vehicles''. This course can be taken also by students from Computer Engineering in the Laurea Magistrale track. | ||
| + | |||
__FORCETOC__ | __FORCETOC__ | ||
==Course Aim & Organization== | ==Course Aim & Organization== | ||
| − | + | ||
| + | Simultaneous estimate of the unknown motion of a camera (or the vehicle this camera is upon) while reconstructing the 3D structure of the observed world is a challenging task that has been deeply studied in the recent literature. The PhD course on ''3D Structure from Visual Motion: Novel Techniques in Computer Vision and Autonomous Robots/Vehicles'' will present modern techniques to simultaneously estimate the unknown motion of a camera while reconstructing the 3D structure of the observed world to be applied in scientific fields such as: 3D reconstruction, autonomous robot navigation, aerial/field surveying, unmanned vehicle maneuvering, etc. | ||
===Teachers=== | ===Teachers=== | ||
| − | Although formally entitled to just one of the teachers the course is held by (in order of appearance) | + | Although formally entitled to just one of the teachers ([http://chrome.ws.dei.polimi.it/index.php/Matt%27s_Home_Page myself]) the course is also held by (in order of appearance) |
* [http://www.dei.polimi.it/people/matteucci Matteo Matteucci] | * [http://www.dei.polimi.it/people/matteucci Matteo Matteucci] | ||
* [http://www.dei.polimi.it/people/caglioti Vincenzo Caglioti] | * [http://www.dei.polimi.it/people/caglioti Vincenzo Caglioti] | ||
| − | * [http://www.dei.polimi.it/people/ | + | <!--* [http://www.dei.polimi.it/people/marcon Marco Marcon]--> |
| − | * [http:// | + | <!--* [http://personal.disco.unimib.it/sorrenti/ Domenico G. Sorrenti]--> |
===Course Schedule=== | ===Course Schedule=== | ||
| − | + | The course schedule for this yeas edition foresees 3 hour lectures from 14:30 to 17:30 (time might change according to participants needs) of the following days: | |
| − | + | ||
| − | + | ||
| − | + | *12/05/2014: Feature extraction, matching and tracking (Matteo Matteucci) | |
| − | * | + | *14/05/2014: Projection model and projection matrix (Vincenzo Caglioti) |
| + | *16/05/2014: Fundamental and Essential matrices (Vincenzo Caglioti) | ||
| + | *19/05/2014: Structure from Motion and Visual Odometry (Vincenzo Caglioti) | ||
| + | *21/05/2014: Simulataneous Localization and Mapping (Matteo Matteucci) | ||
| + | *23/05/2014: Unconventional Visual Odometry: Uncalibrated visual odometry, Omnidirectional odometry (Vincenzo Caglioti) | ||
| + | *26/05/2014: Visual SLAM with filters (Matteo Matteucci) | ||
| + | *28/05/2014: Visual SLAM without filters (Matteo Matteucci) | ||
| − | + | The room for all the lectures is: "Aula Seminari Alessandra Alario" 4th Floor - Building 21 Campus Leonardo. | |
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | <!--In the following you find a tentative syllabus for the course. | |
| − | + | ||
| − | + | ||
| − | + | *'''3d Vision Basics''' | |
| − | * | + | ** Course introduction |
| − | * | + | ** Feature extraction, matching and tracking |
| − | * | + | ** Projection model and projection matrix |
| − | + | ** Fundamental and Essential matrices | |
| − | + | *'''Structure from Motion and Visual Odometry''' | |
| − | * | + | ** Optical flow |
| − | * | + | ** Combined estiamation of 3D structure and camera egomotion |
| − | + | ** Motion extraction and 3D reconstruction | |
| − | + | *'''Unconventional Visual Odometry''' | |
| − | * | + | ** Uncalibrated visual odometry |
| − | + | ** Omnidirectional odometry | |
| − | + | *'''Simulataneous Localization and Mapping''' | |
| − | * | + | ** From Bayesian Filtering to SLAM |
| − | * | + | ** EKF-Based SLAM |
| − | + | *'''Visual SLAM''' | |
| − | + | ** EKF-based Monocular SLAM | |
| − | * | + | ** Stereo and Omnidirectional visual SLAM |
| − | + | ** Why filters? PTAM and FrameSLAM --> | |
| − | + | <!-- | |
| − | * 3D without 3D | + | *'''3D without 3D''' |
| + | ** Plenoptic methods, lumigraph, albedo, non Lambertian surfaces (3h M. Marcon) | ||
| + | --> | ||
==Course Material & Referencies== | ==Course Material & Referencies== | ||
| Line 57: | Line 74: | ||
===Slides and lecture notes=== | ===Slides and lecture notes=== | ||
| + | * [http://home.dei.polimi.it/matteucc/lectures/3DSFVM/FeatureTracking.pdf Correspondence analysis and RANSAC] (2011-2012 ed.) | ||
* [http://home.dei.polimi.it/matteucc/lectures/3DSFVM/MultipleViewGeometry.pdf Camera geometry, single view, and two view geometry material] | * [http://home.dei.polimi.it/matteucc/lectures/3DSFVM/MultipleViewGeometry.pdf Camera geometry, single view, and two view geometry material] | ||
* [http://home.dei.polimi.it/matteucc/lectures/3DSFVM/VisualOdometry.pdf Two view geometry and visual odometry material] | * [http://home.dei.polimi.it/matteucc/lectures/3DSFVM/VisualOdometry.pdf Two view geometry and visual odometry material] | ||
| − | * | + | * [http://home.dei.polimi.it/matteucc/lectures/3DSFVM/FeatureTrackingEgomotion.pdf Optical flow tracking and egomotion estimation] |
| + | * [http://home.dei.polimi.it/matteucc/lectures/3DSFVM/StructureFromMotion.pdf Structure from Motion] | ||
| + | * [http://home.dei.polimi.it/matteucc/lectures/3DSFVM/BayesianFiltering.pdf Bayesian Filtering, Kalman Filtering, and SLAM] | ||
| + | * [http://home.dei.polimi.it/matteucc/lectures/3DSFVM/SLAM.pdf Simultaneous Localization and Mapping] a.k.a. SLAM! | ||
| + | * [http://home.dei.polimi.it/matteucc/lectures/3DSFVM/MonocularSLAM.pdf Monocular SLAM] | ||
| + | * [http://home.dei.polimi.it/matteucc/lectures/3DSFVM/StereoOmniSLAM.pdf Stereo and Omnidirectional SLAM] | ||
| + | * [http://home.dei.polimi.it/matteucc/lectures/3DSFVM/PanoramicVisualOdometry.pdf Panoramic Visual Odomentry] | ||
| + | * [http://home.dei.polimi.it/matteucc/lectures/3DSFVM/PTAM.pdf Parallel Tracking and Mapping] | ||
| + | <!-- * 3D without 3D --> | ||
===Suggested Bibliography=== | ===Suggested Bibliography=== | ||
* R. Hartley, A. Zisserman. [http://www.robots.ox.ac.uk/~vgg/hzbook/index.html Multiple View Geometry in Computer Vision], Cambridge University Press, March 2004. | * R. Hartley, A. Zisserman. [http://www.robots.ox.ac.uk/~vgg/hzbook/index.html Multiple View Geometry in Computer Vision], Cambridge University Press, March 2004. | ||
* S. Thrun, W. Burgard, D. Fox. [http://www.probabilistic-robotics.org/ Probabilistic Robotics], MIT Press, September 2005. | * S. Thrun, W. Burgard, D. Fox. [http://www.probabilistic-robotics.org/ Probabilistic Robotics], MIT Press, September 2005. | ||
| − | * ... | + | * Papers you might find useful to deepen your study: |
| + | ** ''Simultaneous Localization and Mapping (SLAM): Part I The Essential Algorithms''. H. Durrant-Whyte, T. Bailey [http://www.acfr.usyd.edu.au/homepages/academic/tbailey/papers/slamtute1.pdf] | ||
| + | ** ''Unified Inverse Depth Parametrization for Monocular SLAM'' by J.M.M. Montiel, Javier Civera, and Andrew J. Davison [http://www.roboticsproceedings.org/rss02/p11.pdf] | ||
| + | ** ''Parallel Tracking and Mapping for Small AR Workspaces'' by Georg Klein and David Murray [http://www.robots.ox.ac.uk/~gk/publications/KleinMurray2007ISMAR.pdf] | ||
| + | ** ''FrameSLAM: from Bundle Adjustment to Realtime Visual Mappping'' by Kurt Konolige and Motilal Agrawal [http://www.ai.sri.com/~agrawal/frameslam.pdf] | ||
| + | |||
| + | ===Libraries and Demos=== | ||
| + | |||
| + | TBC | ||
| + | |||
| + | == Course Evaluation == | ||
| + | |||
| + | The course evaluation will be done on the basis of a project which could be completed also in groups of two people. In the case of PhD students this project could/should be somehow related to their research interests. | ||
Latest revision as of 23:02, 11 May 2014
Recent news you should be aware of ... * New schedule published with teachers specified * The schedule of 2014 lectures is out! * A new version of the course is scheduled for the year 2013/2014
This is a description page for the PhD course on 3D Structure from Visual Motion: Novel Techniques in Computer Vision and Autonomous Robots/Vehicles. This course can be taken also by students from Computer Engineering in the Laurea Magistrale track.
Contents
Course Aim & Organization
Simultaneous estimate of the unknown motion of a camera (or the vehicle this camera is upon) while reconstructing the 3D structure of the observed world is a challenging task that has been deeply studied in the recent literature. The PhD course on 3D Structure from Visual Motion: Novel Techniques in Computer Vision and Autonomous Robots/Vehicles will present modern techniques to simultaneously estimate the unknown motion of a camera while reconstructing the 3D structure of the observed world to be applied in scientific fields such as: 3D reconstruction, autonomous robot navigation, aerial/field surveying, unmanned vehicle maneuvering, etc.
Teachers
Although formally entitled to just one of the teachers (myself) the course is also held by (in order of appearance)
Course Schedule
The course schedule for this yeas edition foresees 3 hour lectures from 14:30 to 17:30 (time might change according to participants needs) of the following days:
- 12/05/2014: Feature extraction, matching and tracking (Matteo Matteucci)
- 14/05/2014: Projection model and projection matrix (Vincenzo Caglioti)
- 16/05/2014: Fundamental and Essential matrices (Vincenzo Caglioti)
- 19/05/2014: Structure from Motion and Visual Odometry (Vincenzo Caglioti)
- 21/05/2014: Simulataneous Localization and Mapping (Matteo Matteucci)
- 23/05/2014: Unconventional Visual Odometry: Uncalibrated visual odometry, Omnidirectional odometry (Vincenzo Caglioti)
- 26/05/2014: Visual SLAM with filters (Matteo Matteucci)
- 28/05/2014: Visual SLAM without filters (Matteo Matteucci)
The room for all the lectures is: "Aula Seminari Alessandra Alario" 4th Floor - Building 21 Campus Leonardo.
Course Material & Referencies
The following is some suggested material to follow the course lectures.
Slides and lecture notes
- Correspondence analysis and RANSAC (2011-2012 ed.)
- Camera geometry, single view, and two view geometry material
- Two view geometry and visual odometry material
- Optical flow tracking and egomotion estimation
- Structure from Motion
- Bayesian Filtering, Kalman Filtering, and SLAM
- Simultaneous Localization and Mapping a.k.a. SLAM!
- Monocular SLAM
- Stereo and Omnidirectional SLAM
- Panoramic Visual Odomentry
- Parallel Tracking and Mapping
Suggested Bibliography
- R. Hartley, A. Zisserman. Multiple View Geometry in Computer Vision, Cambridge University Press, March 2004.
- S. Thrun, W. Burgard, D. Fox. Probabilistic Robotics, MIT Press, September 2005.
- Papers you might find useful to deepen your study:
- Simultaneous Localization and Mapping (SLAM): Part I The Essential Algorithms. H. Durrant-Whyte, T. Bailey [1]
- Unified Inverse Depth Parametrization for Monocular SLAM by J.M.M. Montiel, Javier Civera, and Andrew J. Davison [2]
- Parallel Tracking and Mapping for Small AR Workspaces by Georg Klein and David Murray [3]
- FrameSLAM: from Bundle Adjustment to Realtime Visual Mappping by Kurt Konolige and Motilal Agrawal [4]
Libraries and Demos
TBC
Course Evaluation
The course evaluation will be done on the basis of a project which could be completed also in groups of two people. In the case of PhD students this project could/should be somehow related to their research interests.
