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Computer Vision Student Seminar
The Computer Vision Student Seminar at the University of Maryland College Park is a student-run series of talks given by current graduate students for current graduate students.
Description[edit]
The purpose of these talks is to:
- Encourage interaction between computer vision students;
- Provide an opportunity for computer vision students to be aware of and possibly get involved in the research their peers are conducting;
- Provide an opportunity for computer vision students to receive feedback on their current research;
- Provide speaking opportunities for computer vision students.
Format[edit]
- An hour-long weekly meeting, consisting of one 20-40 minute talk followed by discussion and food.
- The talks are meant to be casual and discussion is encouraged.
- Topics may include current research, past research, general topic presentations, paper summaries and critiques, or anything else beneficial to the computer vision graduate student community.
Subscribe to the Mailing List[edit]
To receive regular information about the Computer Vision Student Seminar, subscribe to the mailing list by following the instructions here.
Schedule Summer 2011[edit]
All talks take place Thursdays at 4pm in AVW 3450.
| Date | Speaker | Title |
| June 9 | Vlad Morariu | Multi-Agent Event Recognition in Structured Scenarios |
| June 16 | Ajay Mishra | |
| June 23 | (no meeting, CVPR) | |
| June 30 | Dikpal Reddy | |
| July 7 | Raghuraman Gopalan | |
| July 14 | ||
| July 21 | Kaushik Mitra | |
| July 28 | Carlos Castillo | |
| August 4 | ||
| August 11 | ||
| August 18 | ||
| August 25 |
Talk Abstracts[edit]
Multi-Agent Event Recognition in Structured Scenarios[edit]
Speaker: Vlad Morariu -- Date: June 9, 2011
I will present a framework for the automatic recognition of complex multi-agent events in settings where structure is imposed by rules that agents must follow while performing activities. Given semantic spatio-temporal descriptions of what generally happens (i.e., rules, event descriptions, physical constraints), and based on video analysis, the framework determines the events that occurred. Knowledge about spatio-temporal structure is encoded using first-order logic using an approach based on Allen's Interval Logic, and robustness to low-level observation uncertainty is provided by Markov Logic Networks (MLN). The main contribution is that the framework integrates interval-based temporal reasoning with probabilistic logical inference, relying on an efficient bottom-up grounding scheme to avoid combinatorial explosion. Applied to one-on-one basketball, the framework detects and tracks players, their hands and feet, and the ball, generates event observations from the resulting trajectories, and performs probabilistic logical inference to determine the most consistent sequence of events.
Current Seminar Series Coordinators[edit]
Emails are at umiacs.umd.edu.
| Anne Jorstad, jorstad@ | (student of Professor David Jacobs) |
| Sameh Khamis, sameh@ | (student of Professor Larry Davis) |
| Sima Taheri, taheri@ | (student of Professor Rama Chellappa) |
| Ching Lik Teo, cteo@ | (student of Professor Yiannis Aloimonos) |
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