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:

• 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

Presentations on December 14, in MC316, from 9 to 12

• 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.;