The presentations are 15-20 min long, including questions. So plan for 20 minutes to present and 5 min for questions. You should convey the major idea in the paper, you do not (and should not) explain every single little detail.
Some useful points:
Presentations on December 14, in MC316, from 9 to 12
- Give the paper title and the authors on the first slide
- Clearly state the problem the paper tackles
- Explain the prior work on this problem and its limitation (from the prior work section in the paper
- Briefly state which limitations of the prior work the paper proposes to solve and which computational techniques will be used
- Explain the main technical details (the "meat" of the paper)
- Experimental results
- Conclusions (which issues are left to solve, future work, etc...)
- Try to use as many pictures as possible instead of text/formulas
- Roberto Ulloa: "Learning Object Detection from a Small Number of Examples: the Importance of Good Features" by K. Levi and Y. Weiss.
- Yanxin Li: "Automatic design of cascaded classifiers"
by E. Grossmann.
- Wei Li: "Face Age Classification on Consumer Images with Gabor Feature and Fuzzy LDA Method" by F. Gao, H. Ai.
- Zhewei Liang: "Automatic Image Orientation Detection" by A. Vailaya,
H. Zhang, C. Yang, F. Liu, A. K. Jain.
- Junwei Sun: "Recognizing Human Actions: A Local SVM Approach" by C. Schuldt, I. Laptev, B. Caputo.
- Greg Elfers: "Photo and Video Quality Evaluation: Focusing on the Subject" by Y. Luo and X. Tang.
- David De Angelis:
"Extracting Foreground Masks towards Object Recognition" by A. Rosenfeld and D. Weinshall
- Andres Garcia:
"Skin color-based video segmentation under time-varying illumination" by Sigal, L.; Sclaroff, S.; Athitsos, V.;