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Computer Vision Student Seminars

The Computer Vision Student Seminars at the University of Maryland College Park are a student-run series of talks given by current graduate students for current graduate students.

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Description

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.

The guidelines for the format are:

• 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.

Schedule Spring 2015

All talks take place on Thursdays at 3:30pm in AVW 3450.

Date	Speaker	Title
February 19	Bharat Singh	PSPGC: Part-Based Seeds for Parametric Graph-Cuts
February 26	Jingjing Zheng	TBD
March 5	Yezhou Yang	TBD
March 12	Bahadir Ozdemir	TBD
March 19	Spring Break, no meeting
March 26	Sravanthi and Varun Manjunatha	TBD
April 2	Jonghyun (?) or Joe (?)	TBD
April 9	Ang (?) Ching-hui (?)	TBD
April 16	ICCV deadline, no meeting
April 23	Post ICCV deadline, no meeting
April 30	Aleksandr (?)	TBD
May 7	Francisco (?)	TBD
May 14	Final Exam, no meeting

Talk Abstracts Spring 2015

PSPGC: Part-Based Seeds for Parametric Graph-Cuts

Speaker: Bharat Singh -- Date: Feburary 19, 2015

Abstract: PSPGC is a detection-based parametric graph-cut method for accurate image segmentation. Experiments show that seed positioning plays an important role in graph-cut based methods, so, we propose three seed generation strategies which incorporate information about location and color of object parts, along with size and shape. Combined with low-level regular grid seeds, PSPGC can leverage both low-level and high-level cues about objects present in the image. Multiple-parametric graph-cuts using these seeding strategies are solved to obtain a pool of segments, which have a high rate of producing the ground truth segments. Experiments on the challenging PASCAL2010 and 2012 segmentation datasets show that the accuracy of the segmentation hypotheses generated by PSPGC outperforms other state-of-the-art methods when measured by three different metrics(average overlap, recall and covering) by up to 3.5%. We also obtain the best average overlap score in 15 out of 20 categories on PASCAL2010. Further, we provide a quantitative evaluation of the efficacy of each seed generation strategy introduced.

Past Semesters

• Fall 2014
• Spring 2014
• Fall 2013
• Summer 2013
• Spring 2013
• Fall 2012
• Spring 2012
• Fall 2011
• Summer 2011

Funded By

• Computer Vision Faculty
• Northrop Grumman

Current Seminar Series Coordinators

Emails are at umiacs.umd.edu.

Jonghyun Choi, jhchoi@	(student of Professor Rama Chellappa)
Ching-Hui Chen, ching@	(student of Professor David Jacobs)
Austin Myers, amyers@	(student of Professor Yiannis Aloimonos)
Angjoo Kanazawa, kanazawa@	(student of Professor David Jacobs)

Gone but not forgotten.

Raviteja Vemulapalli, raviteja @	(student of Professor Rama Chellappa)
Sameh Khamis
Ejaz Ahmed
Anne Jorstad	now at EPFL
Jie Ni	off this semester
Sima Taheri
Ching Lik Teo

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