Prof. Nassir Navab, Federico Tombari Type: Seminar SWS: 2+0 ECTS: 4 Credits Location: Seminarraum (5613.03.010) Time: 16:00-18:00 Course Language: English
This class is open for Masters and Bachelors students.
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.
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.
Each registered student is required to attend all presentations.
List of Topics
The list of papers from which each student can choose is the following:
Taken: Ivana Jovanovic / Tutor:Federico Tombari — (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
Taken: Karen R. / Tutor:Federico Tombari — (keypoints and features) N. Dalal, B. Triggs, “HoG for Human Detection”, Computer Vision and Pattern Recognition, 2005
Taken: Marat Serahlazau / Tutor:Iro Laina — (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
Taken: Aleksandar Buha / Tutor:Huseyin Coskun — (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
Taken: Wassim Gabriel / Tutor:David Tan — (image classification) Nister, Stewenius, “Scalable Recognition with a Vocabulary Tree”, CVPR 2006
Taken: Shuwei Hu / Tutor:Huseyin Coskun — (image classification) B. Leibe, A. Leonardis, B. Schiele, “Robust Object Detection by Interleaving Categorization and Segmentation”, International Journal of Computer Vision, 2008
Taken: Krishen Kant Kandwal / Tutor:Iro Laina — (face detection) P. Viola, M. Jones, “Rapid object detection using a boosted cascade of simple features”, CVPR 2001
Taken: José Pedro Santos / Tutor:David Tan — (human pose) J. Shotton et al., "Real-Time Human Pose Recognition in Parts from a Single Depth Image", CVPR 2011
Taken: Ralitsa Dimitrova / Tutor:Keisuke Tateno — (reconstruction) R. Newcombe et al., "KinectFusion: Real-Time Dense Surface Mapping and Tracking", ISMAR 2011