Bachelor Seminar:
Foundations of Computer Vision

Prof. Nassir Navab, Federico Tombari, Vasileios Belagiannis, Felix Achilles, Wadim Kehl, Benjamin Busam

Type: Seminar Module IN0014
SWS: 2+0
ECTS: 4 Credits
Location: MI 03.13.010
Time: Wednesday 16:00-18:00
Course Language: English

Announcements

• [3.11.2014] The list of papers has been published
• [16.10.2014] If interested to the course, register here
• [16.10.2014] Initial meeting will be held on Tuesday, 04.11.2014, in MI 03.13.010 from 14:00 to 15:00.
  
• [16.10.2014] The list of papers will be online one day before the initial meeting.

Introduction

• The Seminar Course concerns fundamental methods in the field of Computer Vision. The Seminar will propose a list of scientific articles related to the fundamental research topics of Computer Vision, such as keypoint detection, segmentation, 3D object detection, image classification, camera calibration and optical flow.

Registration

• Registration can be performed through TUM online.
• Write a short email indicating your interest on the course to tombari@in.tum.de

Requirements

In this Seminar, each student is asked to select one paper from a list. In order to successfully complete the seminar, participants have to fulfill these requirements:

• Presentation: The selected paper is presented to the other participants (25 minutes presentation, 15 minutes questions). Use the CAMP templates for PowerPoint CAMPmaster.pot, or Latex: CAMP-latex-template.zip.
• Written Handout: A document of maximum 8 pages is written and submitted one week after the presentation. Please download and use the llncs2e.zip Latex template.
• Attendance: Participants have to participate actively in all seminar sessions.

The students are required to attend each seminar presentation which will be held during this course. Each presentation is followed by a discussion and everyone is encouraged to actively participate. The handout must include all references used and must be written completely in your own words. Copy and paste will not be tolerated. Both handout and presentation have to be done in English.

List of Topics

The list of papers from which each student can choose is the following:

• (image filtering) C. Tomasi, R. Manduchi, “Bilateral filtering for gray and color images”, ICCV 1998
• (optical flow) B. D. Lucas, T. Kanade, “An iterative image registration technique with an application to stereo vision”, Imaging Understanding Workshop, 1981
• (calibration) Z. Zhang, “A flexible new technique for camera calibration”, IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(11):1330-1334, 2000
• (keypoints and features) D.G. Lowe, "Distinctive image features from scale-invariant keypoints", International Journal of Computer Vision, 2004
• (keypoints and features) N. Dalal, B. Triggs, “HoG for Human Detection”, Computer Vision and Pattern Recognition, 2005
• (object detection) P.F. Felzenszwalb, R.B. Girshick, D. McAllester^?, D. Ramanan, “Object Detection with Discriminatively Trained Part Based Models”, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010
• (segmentation and tracking) D. Comaniciu, P. Meer, "Mean Shift: A Robust Approach Toward Feature Space Analysis". IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002
• (image classification) Nister, Stewenius, “Scalable Recognition with a Vocabulary Tree”, CVPR 2006
• (image classification) B. Leibe, A. Leonardis, B. Schiele, “Robust Object Detection by Interleaving Categorization and Segmentation”, International Journal of Computer Vision, 2008
• (face detection) P. Viola, M. Jones, “Rapid object detection using a boosted cascade of simple features”, CVPR 2001

The slides for the introductory meeting are available here.

Schedule

This is the final schedule for the course. Each registered student is required to attend all presentations.

Date	Time	Room	Topic	By	Supervision	Material
10.12	4:00-4:40 pm	Seminarraum 03.13.010	Scalable Recognition with a Vocabulary Tree	Patrick Reto	Wadim Kehl
10.12	4:40-5:20 pm	Seminarraum 03.13.010	Robust Object Detection by Interleaving Categorization and Segmentation	Temmuz Karali	Felix Achilles
10.12	5:20-6:00 pm	Seminarraum 03.13.010	Bilateral Filtering for Gray and Color Images	David Labode	Felix Achilles
17.12	4:00-4:40 pm	Laborraum 03.13.008	Mean Shift: A Robust Approach Toward Feature Space Analysis	Benjamin Schmithüsen	Wadim Kehl
17.12	4:40-5:20 pm	Laborraum 03.13.008	Rapid object detection using a boosted cascade of simple features	Christos Stoilas	Benjamin Busam	Report Presentation
17.12	5:20-6:00 pm	Laborraum 03.13.008	Distinctive image features from scale-invariant keypoints	Amin Ahantab	Benjamin Busam	Report Presentation