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teaching:ws2018:visnav_ws2018 [2018/06/20 12:18] Nikolaus Demmel |
teaching:ws2018:visnav_ws2018 [2018/10/26 16:51] usenko |
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Please direct questions to [[visnav_ws2018@vision.in.tum.de]] | Please direct questions to [[visnav_ws2018@vision.in.tum.de]] | ||
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TUMOnline course entry: https:// | TUMOnline course entry: https:// | ||
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== Date & Location == | == Date & Location == | ||
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- | Lecture & exercises (assignment phase) : Mondays, lectures approx. 2pm to 4pm in seminar room 02.09.023, tutoring of exercises approx. 4pm to 6pm in lab 02.05.014 \\ | + | Lecture & exercises (assignment phase) : Mondays, lectures approx. 2pm to 4pm in 02.05.014, tutoring of exercises approx. 4pm to 6pm in 02.05.014 \\ |
Tutored lab time (project phase) : Mondays from 2pm to 6pm in lab 02.05.014 (other times for free project work available, tbd) \\ | Tutored lab time (project phase) : Mondays from 2pm to 6pm in lab 02.05.014 (other times for free project work available, tbd) \\ | ||
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== Course Structure == | == Course Structure == | ||
- | The course will take place in our seminar room 02.09.023 and in lab room 02.05.014. In the beginning phase (4-5 weeks), there will be introductory lectures in seminar | + | The course will take place in the lab room 02.05.014. In the beginning phase (4-5 weeks), there will be introductory lectures in room 02.05.014. Programming assignment sheets on basic problems will be handed out every week. In a second phase, the students will work in teams of 2-3 students on a practical problem (project). For the rest of the semester, the group meets weekly with their tutors and presents and discusses their progress. At the end of the course, the teams will present their project in a talk and demonstrate their solutions. They will document their project work in a written report. Both the assignments and the project part will be graded, and a final grade will be obtained from that. |
For more details see //Course Layout// below.\\ | For more details see //Course Layout// below.\\ | ||
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===== Literature ===== | ===== Literature ===== | ||
- | Lecture notes: | + | Relevant courses: |
* Computer Vision II: Multiple View Geometry, http:// | * Computer Vision II: Multiple View Geometry, http:// | ||
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+ | The following book also covers many aspects. You should focus on Part II and III and selected background from Part I as needed: | ||
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+ | * Timothy D. Barfoot, "State Estimation for Robotics", | ||
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+ | Free pdf available: http:// | ||
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+ | Less relevant, but still helpful: | ||
* Autonomous Navigation for Flying Robots (EdX course), http:// | * Autonomous Navigation for Flying Robots (EdX course), http:// | ||
* Computer Vision I: Variational Methods, http:// | * Computer Vision I: Variational Methods, http:// | ||
Selected publications: | Selected publications: | ||
- | * Direct Sparse Odometry (J. Engel, V. Koltun, D. Cremers), In Trans. on Pattern Analysis and Machine Intelligence, 2017. | + | * Edward Rosten et al., " |
- | * Semi-Dense Visual Odometry for AR on a Smartphone (T. Schöps, J. Engel, D. Cremers), In International Symposium on Mixed and Augmented Reality, 2014. | + | * Michael Calonder et al., " |
- | * From Monocular SLAM to Autonomous Drone Exploration, | + | * Ethan Rublee et al., "ORB: an efficient alternative to SIFT or SURF" (http://www.willowgarage.com/ |
- | * Collision Avoidance | + | * Raúl Mur-Artal et al., " |
+ | * Ethan Eade, "Lie Groups | ||
===== Slides ===== | ===== Slides ===== | ||
- | Additional material can be downloaded from [[teaching: | + | Additional material can be downloaded from [[teaching: |