Difference between revisions of "Stefan Karlsson/PersonalPage/Education/MultiScaleCourse"

From ISLAB/CAISR
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This is the web page for the course '''Multiscale and Multidimensional Analysis'''.The course description will be available on the official university site soon. The schedule for the course will be made ad hoc, using doodle or by agreement over email.
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This is the web page for the course '''Multiscale and Multidimensional Analysis'''. The course description will be available on the official university site soon. The schedule for the course will be made ad hoc, using doodle or by agreement over email.
  
 
Reach us at Stefan.Karlsson(AHTT)hh.se or feralo(AHTT)hh.se for any questions.
 
Reach us at Stefan.Karlsson(AHTT)hh.se or feralo(AHTT)hh.se for any questions.
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===Course organization===
 
===Course organization===
There will be roughly one new exercise made available to you for every session, and there will be a total of 4 Exercises including a small project. For each exercise there are several tasks for you to perform. These are to be completed and discussed during the sessions. Instructions on how to report on them will be given in the descriptions for the excercises. Communication '''WILL NOT''' be done through blackboard.  
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There will be roughly one new exercise made available to you for every session, and there will be a total of 4 exercises including a project. For each exercise there are several tasks for you to perform. These are to be completed and discussed during the sessions. Instructions on how to report on them will be given in the descriptions for the exercises. Communication '''WILL NOT''' be done through blackboard.  
  
=Exercises and sessions (files will be made available shortly)=
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=Exercises and sessions (files will be made available before each session)=
1. [[Media:MultiScaleApproaches.pdf|Linear scale space]] (Stefan) -1 WEEK
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1. [[Media:MultiScaleApproaches.pdf|'''Linear scale space''']] (Stefan): 1 WEEK
  
- Waveletets (Gabor, Mexican Hat)  
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* Waveletets (Gabor, Mexican Hat)  
  
- Pyramids (Gaussian, Laplacian, etc.)  
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* Pyramids (Gaussian, Laplacian, etc.)  
  
- Median filtering  
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* Median filtering  
  
- [[Media:MultiDimE1.zip|ONE PRACTICAL ASSIGNMENT ON THIS]]   
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→ [[Media:MultiDimE1.zip|PRACTICAL ASSIGNMENT]]   
  
  
  
2. Directionality analysis (Fernando) -1 WEEK  
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2. '''Directionality analysis''' (Fernando): 1 WEEK  
  
- Structure tensor, HOGs, Gabor  
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* Structure tensor, HOGs, Gabor  
  
- Edges, corners  
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* Edges, corners  
  
  
3. Non-linear scale-space (Stefan) -1.5 WEEK  
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3. '''Non-linear scale-space''' (Stefan): 1.5 WEEK  
  
- Variational formulations  
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* Variational formulations  
  
- Non-linear filtering  
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* Non-linear filtering  
  
- De-noising  
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* De-noising  
  
- ONE PRACTICAL ASSIGNMENT ON THIS
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→ PRACTICAL ASSIGNMENT
  
  
4. Feature analysis (Fernando) -1.5 WEEK  
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4. '''Feature analysis''' (Fernando): 1.5 WEEK  
  
- Segmentation, clustering  
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* Segmentation, clustering  
  
- Feature extraction, pattern matching and classification  
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* Feature extraction, pattern matching and classification  
  
- ONE PRACTICAL ASSIGNMENT ON THIS
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→ PRACTICAL ASSIGNMENT
  
  
5. Applications for computer vision/object detection (Fernando, Stefan) - 1 WEEK  
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5. '''Applications for computer vision/object detection''' (Fernando, Stefan): 1 WEEK  
  
- SIFT  
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* SIFT  
  
- Viola-Jones  
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* Viola-Jones  
  
- Perona-Malik  
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* Perona-Malik  
  
- FINAL PROJECT ASSIGNMENT
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→ FINAL PROJECT ASSIGNMENT

Revision as of 15:32, 7 January 2015

This is the web page for the course Multiscale and Multidimensional Analysis. The course description will be available on the official university site soon. The schedule for the course will be made ad hoc, using doodle or by agreement over email.

Reach us at Stefan.Karlsson(AHTT)hh.se or feralo(AHTT)hh.se for any questions.

News

No news yet

Course organization

There will be roughly one new exercise made available to you for every session, and there will be a total of 4 exercises including a project. For each exercise there are several tasks for you to perform. These are to be completed and discussed during the sessions. Instructions on how to report on them will be given in the descriptions for the exercises. Communication WILL NOT be done through blackboard.

Exercises and sessions (files will be made available before each session)

1. Linear scale space (Stefan): 1 WEEK

  • Waveletets (Gabor, Mexican Hat)
  • Pyramids (Gaussian, Laplacian, etc.)
  • Median filtering

PRACTICAL ASSIGNMENT


2. Directionality analysis (Fernando): 1 WEEK

  • Structure tensor, HOGs, Gabor
  • Edges, corners


3. Non-linear scale-space (Stefan): 1.5 WEEK

  • Variational formulations
  • Non-linear filtering
  • De-noising

→ PRACTICAL ASSIGNMENT


4. Feature analysis (Fernando): 1.5 WEEK

  • Segmentation, clustering
  • Feature extraction, pattern matching and classification

→ PRACTICAL ASSIGNMENT


5. Applications for computer vision/object detection (Fernando, Stefan): 1 WEEK

  • SIFT
  • Viola-Jones
  • Perona-Malik

→ FINAL PROJECT ASSIGNMENT