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
 +
 +
<!--
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  * 17/05/2012: Change in the lecture topics in the schedule
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  * 18/04/2012: Change of Fri 20/04 room: lecture will be in D2.2
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  * 11/04/2012: Rooms for classes updated and first class material published.
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  * 18/03/2012: Detailed course schedule published!
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  * 06/03/2012: Detailed course schedule coming out soon if you did not received the notification email please contact me!
 +
-->
 +
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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==
This is a description page for the PhD course on ''3D Structure from Visual Motion: Novel Techniques in Computer Vision and Autonomous Robots/Vehicles''. It is meant to present modern techniques to simultaneously estimate the unknown motion of a camera while reconstructing the 3D structure of the observed world to be applied un scientific fields such as: 3D reconstruction, autonomous robot navigation, aerial/field surveying, unmanned vehicle maneuvering, etc.
+
 
 +
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.idsia.ch/~migliore/ Davide Migliore]
 
 
* [http://www.dei.polimi.it/people/caglioti Vincenzo Caglioti]
 
* [http://www.dei.polimi.it/people/caglioti Vincenzo Caglioti]
* [http://www.dei.polimi.it/people/marcon Marco Marcon]
+
<!--* [http://www.dei.polimi.it/people/marcon Marco Marcon]-->
* [http://personal.disco.unimib.it/sorrenti/ Domenico G. Sorrenti]
+
<!--* [http://personal.disco.unimib.it/sorrenti/ Domenico G. Sorrenti]-->
  
 
===Course Schedule===
 
===Course Schedule===
  
This is the schedule foreseen for the course. The timing refers to the duration of the room reservation not necessarily the duration of the lecture ;-)
+
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:
  
*'''15/02/2010 14:30-18:30 in Sala Seminari DEI'''
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*12/05/2014: Feature extraction, matching and tracking (Matteo Matteucci)
** Course introduction (M. Matteucci)
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*14/05/2014: Projection model and projection matrix (Vincenzo Caglioti)
** Correspondence analysis: tracking and ransac (D. Migliore)
+
*16/05/2014: Fundamental and Essential matrices (Vincenzo Caglioti)
** Optical flow (D. Migliore)
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*19/05/2014: Structure from Motion and Visual Odometry (Vincenzo Caglioti)
*'''17/02/2010 14:30-18:30 in Aula PT1 DEI'''
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*21/05/2014: Simulataneous Localization and Mapping (Matteo Matteucci)
** Projection model and projection matrix (V. Caglioti)
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*23/05/2014: Unconventional Visual Odometry: Uncalibrated visual odometry, Omnidirectional odometry (Vincenzo Caglioti)
** Fundamental and Essential matrices (V. Caglioti)
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*26/05/2014: Visual SLAM with filters (Matteo Matteucci)
*'''22/02/2010 14:30-18:30 in Sala Seminari DEI'''
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*28/05/2014: Visual SLAM without filters (Matteo Matteucci)
** Motion extraction and 3D reconstruction (V. Caglioti)
+
 
*'''24/02/2010 14:30-18:30 in Sala Seminari DEI'''
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The room for all the lectures is: "Aula Seminari Alessandra Alario" 4th Floor - Building 21 Campus Leonardo.
**Uncalibrated visual odometry (V. Caglioti)
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**Omnidirectional odometry (V. Caglioti)   
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<!--In the following you find a tentative syllabus for the course.
*'''26/02/2010 14:30-18:30 in Sala Seminari DEI'''
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** Combined estiamation of 3D structure and camera egomotion (M.Marcon)
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*'''3d Vision Basics'''
*'''01/03/2010 14:30-18:30 in Aula PT1'''
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** Course introduction
** Bayesian Filtering and SLAM (M. Matteucci)
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** Feature extraction, matching and tracking
*'''03/03/2010 14:30-18:30 in Aula PT1 DEI'''
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** Projection model and projection matrix  
** MonoSLAM, PTAM and FrameSLAM (M. Matteucci, D.G. Sorrenti)
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** Fundamental and Essential matrices
*'''05/03/2010 14:30-18:30 in Sala Seminari DEI'''
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*'''Structure from Motion and Visual Odometry'''  
** 3D without 3D: plenoptic methods, lumigraph, albedo, non Lambertian surfaces (M. Marcon)
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** 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
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*'''Visual SLAM'''  
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** EKF-based Monocular SLAM
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** Stereo and Omnidirectional visual SLAM
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** Why filters? PTAM and FrameSLAM -->
 +
<!--
 +
*'''3D without 3D'''  
 +
** Plenoptic methods, lumigraph, albedo, non Lambertian surfaces (3h M. Marcon)
 +
-->
  
 
==Course Material & Referencies==
 
==Course Material & Referencies==
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===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/FeatureTracking.pdf Correspondence analysis and RANSAC]
 
 
* [http://home.dei.polimi.it/matteucc/lectures/3DSFVM/FeatureTrackingEgomotion.pdf Optical flow tracking and egomotion estimation]
 
* [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/StructureFromMotion.pdf Structure from Motion]
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* [http://home.dei.polimi.it/matteucc/lectures/3DSFVM/PanoramicVisualOdometry.pdf Panoramic Visual Odomentry]
 
* [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]
 
* [http://home.dei.polimi.it/matteucc/lectures/3DSFVM/PTAM.pdf Parallel Tracking and Mapping]
* 3D without 3D
+
<!-- * 3D without 3D -->
  
 
===Suggested Bibliography===
 
===Suggested Bibliography===
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* 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:
 
* 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]
** 'FrameSLAM: from Bundle Adjustment to Realtime Visual Mappping' by Kurt Konolige and Motilal Agrawal [http://www.ai.sri.com/~agrawal/frameslam.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 22:02, 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.


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

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.