CSUMS………………………. 1

VISITORS .............................. 2

2008 & 2009 GRADUATES ........ 3
BI-ANNUAL REPORT 2008 & 2009
COMPUTER VISION LAB
RESEARCH ............................ 4-5

COMPUTER VISION LAB
PUBLICATIONS 2008 & 2009 .. 6-7

GUEST SPEAKERS ................. 8
Computational Science Training for Undergraduates
in the Mathematical Sciences (CSUMS)
With an Emphasis on Computer Vision and Imaging Science
On September 16, 2008 the National Science Foundation
awarded a grant (in the amount of $585,198 for a 3 year period
with a possible extension of two more years with additional
funding of
$395,126) entitled “CSUMS: Computational
Mathematics with Emphasis on Computer Vision and Imaging
Science”
Professor
Mubarak Shah as PI
and Profs. Constance
M. Schober, Niels da
Vitoria Lobo, Piotr
Mikusinski and Xin Li
as co-PIs.
Our CSUMS has a cohort of 10 participants per year, for five years.
We are currently in the second year of the program. The key
distinctive elements of our approach are (1) to have a full year
training in carefully designed course work so that the participants
can master the mathematical and computational fundamentals, (2) to
engage each participant in
a meaningful research
project integrated into the
year-long program, (3) to
present each participant
with several possible
project topics, so that they
can feel they have chosen
a project which is most
interesting to them, (4) to
immerse the participants
in the general research
environment essentially as
if they were graduate
students, and (5) to
develop the participants’
skills in communicating
scientific ideas in writing
2009 GAUSS Group (from left to right): Dr. Xin Li, Dr. Robert Muise,
and oral presentations by
Dr. Mubarak Shah, Devina Shiwlochan, Dr. Connie Schober, Laura Norena, Leon Guerrero,
presenting at professional
Dr. Piotr Mikusinski, Maria Villareal, Christopher Huff, Maria Boak, Johann Veras,
meetings.
Steven Schraudner, Dr. Lobo
The Department of
Mathematics is heading
this project in which a
team effort of faculty
members from math,
computer
science,
education and industry
will introduce a yearlong
computational
mathematics research
and training program
based on the successes
and experience of the
team in undergraduate
research (NSF REU) in
computer vision and imaging science over the past twenty years.
With a year-long training program in computational mathematics
using exciting applications of mathematics in images and videos
as motivating examples, it is possible to provide participants with
a solid background in both mathematical theory and problem
solving techniques to pursue careers and graduate study in fields
that require integrated strengths in computation and the
mathematical sciences. The project restructures and improves
the current curriculum in computational mathematics track at
UCF, making impact on a wide range of students.
The first cohort of
CSUMS participants have completed the inaugural year of the
program. Maria Boak and Christopher Huff both graduated and
were accepted to the Ph.D. program at UCF. Devina Shiwlachon
also graduated and has applied to the pre-med and bioinformatics
graduate programs. For more information, please visit http://
www.math.ucf.edu/csums.
-1-
Group
Computer Vision Lab
University of Central Florida
Dr. Mubarak Shah
Agere Chair Professor
Director, Computer Vision Lab
Ms. Cherry Place
Laboratory Manager
Research Associates
Dr. Shandong Wu
Ph.D. Students
Subhabrata Bhattacharya
Haroon Idrees
Hamid Izadinia
Salman Khokhar
Baoyuan Liu
Ramin Mehran
Omar Oreifej
Enrique Ortiz
Ryan Patrick
Kishore Reddy
Vladimir Reilly
Imran Saleemi
Guang Shu
Berkan Solmaz
Imran Naveed Syed
Gonzalo Vaca
Yang Yang
Amir Roshan Zamir
B.S. Students
Ada Brewton
Arian Caraballo
Joshua DuLac
David Krauser
Ryan McEachin
Daniela Zicavo
High School Students
Nelson Tan
From left to right: Ramin Mehran, Guang Shu, Shandong Wu, Kishore Reddy, Yang Yang, Arjun Nagendran, Naveed Imran Syed,
Berkan Solmaz, Imran Saleemi, Vladimir Reilly, Mubarak Shah, Soumyabrata Dey, Mikel Rodriguez, Aditya Gupta, Subhabrata
Bhattacharya, Jonathan Poock, Jingen Liu, Haroon Idrees, Enrique Ortiz, Josh DuLac, Omar Oreifej, Gopi, Vajravelu
The picture was taken in September 2009.
Visiting Scholars
Zahid Riaz
Xiaoguang Di
Ph.D. student working
with Profs. Bernd Radig
and Micheal Beetz at the
Technical University of
Munich. Worked with
the UCF Vision lab on
Human Tracking and
Action Recognition from December 2009
through April 2010. Riaz was thankful for the
lab’s cooperation during his stay and hopes to
be in contact in the future for collaboration.
Associate Professor from
Harbin Institute of Technology received funding from the
China Scholarship Council to
study abroad for twelve
months. Di arrived to the
Computer Vision Lab in December 2009 and has been pursuing Computer
Vision and Image Processing research.
Marco Zini
Wang Yong
Student working with
Professor Rita Cucchiara
at Modena University,
Modena, Italy.
He
came to the Computer
Vision Lab in November
2009 for six months to
work on his M.S. thesis related to tracking in
high density crowds.
Ph.D. Candidate from Shanghai Jiao Tong University also
received funding from the
China Scholarship Council to
visit the Computer Vision Lab
to complete his work on
“Multiple Cameras for Scene
Understanding and Object Tracking”. Yong
arrived in September 2009 and has recently
extended his visit until December 2010.
-2-
Computer Vision Lab Graduates
Ph. D.
Saad Khan
Saad Ali
Arslan Basharat
Topic: Multi-view Approaches to Tracking,
3D Reconstruction & Object Class Detection
Graduation Term: Spring 2008
Current Affiliation: Sarnoff Corporation
Topic: Taming Crowded Visual Scenes
Graduation Date: Spring 2008
Current Affiliation: Sarnoff Corporation
Topic: Modeling Scenes and Human
Activities in Videos
Graduate Term: Spring 2009
Current Affiliation: Kitware, Inc.
Jingen Liu
Pavel Babenko
Topic: Learning Semantic Features for Visual Topic: Visual Inspection of Railroad Tracks
Recognition
Graduation Term: Spring 2009
Graduate Term: Spring 2009
Current Affiliation: Madison Research TechCurrent Affiliation: Sarnoff Corporation
nologies
M.S.
Yusuf Aytar
Ryan Faircloth
Philip Berkowitz
Topic: Semantic Video Retrieval Using
High-level Context
Graduation Term: Spring 2008
Current Affiliation: Oxford University
Topic: Combining Audio and Video Tempo
Analysis for Dance Detection
Graduation Term: Summer 2008
Topic: A Statistical Approach to View
Synthesis
Graduation Date: Summer 2009
Current Affiliation: DRS
B.S. (Honors in the Major)
Brandyn White
Topic: Using FPGAs to Perform Embedded
Image Registration
Graduation Term: Summer 2009
Current Affiliation: University of Maryland
-3-
UCF Researcher Developing Computer Program to Detect,
Measure Brain Tumors
The same techniques used to detect suspicious activity in airports, stadiums and other public places are now being used by the UCF researcher
who invented them to find and measure potentially life-threatening brain tumors. Mubarak Shah, UCF’s Agere Chair professor of Computer
Science and one of the world’s most eminent researchers in the rapidly developing field of computer imaging, has received $400,000 from the
National Institutes of Health to develop a computer program to analyze brain scans produced by magnetic resonance imaging (MRI.). The twoyear grant funded in May 2009 is the first UCF has received from money allocated by the American Recovery and Reinvestment Act stimulus
program. The funding will enable Shah and his collaborators -- Dr. Nicholas Avgeropoulos, a neuro-oncologist with Orlando Health System,
and Dr. David Rippe, a neuroradiologist with Sunshine Radiology at Florida Hospital Zephyrhills
-- to work together on the complex task of automatically measuring and comparing the size of a
tumor in 3D from MRI scans.
Nearly a decade ago, Shah approached Rippe, who at that time was chairman of the radiology
department at Florida Hospital Orlando, looking for ways to use computer technology to help
those in the medical profession. The alliance was “a natural fit,” Rippe said. “Radiologists use
computers to look at scans, but this is taking the next step – allowing computers to help radiologists analyze the pictures and enabling an automated method to calculate the size of tumors,” he
said. Radiologists are typically hindered in their analyses by a variety of factors, such as tumors
that are irregular in shape or have jagged edges, tumors with liquefied centers, or surrounding
tissue that is deformed or changing shape. “Not only are the changes visually hard to see, we also
want numbers to quantify the types of changes we are talking about,” Rippe said. Those numbers
help determine whether a particular treatment plan such as radiation or chemotherapy is working.
Dr. David Rippe
Automated analysis of a small data set using Shah’s preliminary method has been shown to be up to 90 percent accurate compared to the analyses provided by the radiologists. Shah said some of the challenges include making sure the typically low-resolution scans can be converted to
the high-resolution images needed for computers to precisely measure tumors. He also must perform extensive experiments with a large data set
to validate his method. He has partnered with a UCF biostatistician, Xiaogang Su, to ensure that the measurements are statistically correct.
Shah’s work has typically focused on analyzing images for signs of suspicious or dangerous behaviors or threats. While at UCF, he has received
more than $7.5 million in funding for projects ranging from visual monitoring of railroad grade crossings for the Department of Transportation
to automatic classification and analysis of reconnaissance videos for the Department of the Interior. (Courtesy of UCF Newsroom)
UCF-50 Dataset
UCF50 is an action recognition dataset with 50 action categories, consisting of realistic videos taken
from YouTube. This dataset is an extension of the YouTube Action dataset which has 11 action categories. The dataset can be downloaded from the following address: http://vision.eecs.ucf.edu/
datasetsActions.html#UCF50.
Most of the available action recognition datasets are not realistic and are staged by actors. In our dataset,
the primary focus is to provide the computer vision community with an action recognition dataset consisting of realistic videos which are taken from YouTube. Our dataset is very challenging due to large
variations in camera motion, object appearance and pose, object scale, viewpoint, background clutter,
illumination conditions, etc. For all of the 50 categories, the videos are divided into 25 groups, where
each group consists of more than 4 action clips. The video clips in the same group may share some common features, such as the same person, similar background, similar viewpoint, and so on.
STATESS
In December of 2009, the National Science Foundation (NSF) awarded a grant of $599,973 to the University of Central Florida for a project
entitled “Students Actualizing Talent at Education’s Subsequent Stages (STATESS),” Professor Mubarak Shah, as PI and Brian Moore,
Niels da Vitoria Lobo and Xin Li as co-PIs. The award is effective January 1, 2010 and expires December 31, 2013. This project offers up to
twenty scholarships per year in the range of $4,000 to $10,000 per year for recent undergraduate and transfer students and first year graduate
students in Mathematics and Computer Science as well as in other Science, Technology, Engineering, and Mathematics (STEM) fields. These scholarships are renewable up to four years, and they are intended for students that might not have the opportunity to attend university otherwise. Scholarship recipients will be privileged to several resources and activities that are intended to ensure the student’s success in completing their undergraduate or graduate degrees.
-4-
AAAS Elects Shah as a Fellow
Dr. Mubarak Shah was named fellow by one of the world’s largest and most wellrespected scientific societies, the American Association for the Advancement of Science
(AAAS) in November 2009. He was among 531 people nationwide and 4 professors at
UCF to be selected by their peers for scientifically or socially distinguished efforts to
advance science or its applications.
“To have our faculty members recognized by their peers for outstanding achievements in
science and engineering is an honor for our entire university community,” said M.J.
Soileau, Vice President for Research and Commercialization. “In classrooms and laboratories throughout our university, students are working with world-class professors who
are leaders in their fields. UCF has long recognized the achievements of these scholars,
and it is great to see them earn well-deserved national recognition.”
Dr. Diane Chase, Dr. Debra Reinhart, Dr. Mubarak Shah
Shah, UCF’s Agere Chair Professor of Computer Science, was selected for his outstanding contributions to video surveillance and monitoring,
shape from shading, active contours, human action recognition and object tracking in computer vision. He was recognized on February 20, 2010
during the AAAS annual meeting in San Diego and was also included in the AAAS News & Notes section of the journal Science on December
18, 2009. (Courtesy of UCF Newsroom)
UCF Teaches Aspiring Computer Vision Researchers from
Around the Country
In 2008, 11 students from across the country were involved in the University of Central Florida’s (UCF) annual Research Experience for Undergraduates in Computer Vision funded by the National Science Foundation. This year’s group included five students from UCF and six other undergraduates from schools such as the University of Florida, University of Southern California and Rice University.
During the summer months, when most students are thinking about anything but schoolwork, UCF hosts Research Experience for Undergraduate
(REU) program in disciplines ranging from nanotechnology and machine learning to computer vision and optics. The programs aim to encourage undergraduates to pursue research endeavors and graduate school. During the past two decades, nearly 200 undergraduates from schools all
over the nation have taken part in the Computer Vision program, UCF’s longest running—going on 21 years. Its participants have co-authored
more than 60 research papers, and six are now faculty members at universities.
During 2008’s summer program participants attended introductory computer vision classes and conducted research in UCF labs. Students
worked individually on projects ranging from video retrieval to image enhancement to robotics.
In the fall, they continued their research projects and gathered together twice more during the school year to review and discuss their endeavors.
By the end of the academic year, students had to write a comprehensive report describing their project and could choose to submit their findings
to a science paper or journal. Chabra, a junior at USC who is originally from Long Island, NY, is contributing to UCF’s TRECVid project.
TRECVid aims to solve the problem of locating specific
segments of footage in long-running videos. According to
Chabra, the UCF program has led him to consider future
career paths in the industry and academia. Whatever he
decides, Chabra said that “after finishing up my undergraduate studies, I would definitely like to go to graduate
school.”
Director Mubarak Shah believes that the Research Experience for Undergraduates program is great exposure for
students who want to excel in the computer vision field.
“The program has contributed to science and engineering
by exposing undergraduates to the excitement and challenge of research,” Shah said. “Due to that, roughly half of
the students have gone on to graduate school.”
UCF’s Computer Vision Lab has received more than $1.2
million from the NSF to encourage promising students’
interests in science for the past 21 years. (Courtesy of UCF
Newsroom)
2008 REU Group (from left to right): Dr. Mubarak Shah, Jason Hochreiter, Cynthia Atherton, Sarah
Applegate, Steven Braeger, Ajay Chabra, Dr. Marshall Tappen, Karthik Prabhakar, Joshua Hartman,
Lam Tran, Nicholas Hirsch, Alexis Oyama, Dr. Niels Lobo
-5-
2008 & 2009 Publications & Invited Talks
BOOK
Omar Javed and Mubarak Shah, Automated Multi Camera Surveillance: Algorithms and Practice, Springer, September 2008.
Jingen Liu, Saad Ali, and Mubarak Shah,
Recognizing Human Actions Using
Multiple Features, IEEE Conference on
Computer Vision and Pattern Recognition, Anchorage, Alaska 2008.
Jingen Liu, Yang Yang and Mubarak
Shah, Learning Semantic Visual Vocabularies Using Diffusion Distance, IEEE
Conference on Computer Vision and Pattern Recognition, Miami, Florida, 2009.
Pingkun Yan, Saad M. Khan, and Mubarak Shah, Learning 4D Action Feature
Models for Arbitrary View Action
Recognition, IEEE Conference on Computer Vision and Pattern Recognition,
Anchorage, Alaska 2008.
Jingen Liu, Jiebo Luo and Mubarak Shah,
Recognizing Realistic Actions from Videos ‘in the Wild’, IEEE Conference on
Computer Vision and Pattern Recognition, Miami, Florida, 2009.
BOOK CHAPTER
Yaser Sheikh, Omar Javed and Mubarak
Shah, Object Association Across Multiple Cameras, in Multi-camera Networks:
Concepts and Applications, Elsevier, editors Hamid Aghajan and Andrea Cavallaro, 2009.
CONFERENCES
Mikel D. Rodriguez, Javed Ahmed, and
Mubarak Shah, Action MACH: A Spatiotemporal Maximum Average Correlation
Height Filter for Action Recognition,
IEEE Conference on Computer Vision
and Pattern Recognition, Anchorage,
Alaska 2008.
Saad M. Khan, and Mubarak Shah, Reconstructing Non-stationary Articulated
Objects in Monocular Video using Silhouette Information, IEEE Conference
on Computer Vision and Pattern Recognition, Anchorage, Alaska 2008.
Jingen Liu, and Mubarak Shah, Learning
Human Actions via Information Maximization, IEEE Conference on Computer
Vision and Pattern Recognition, Anchorage, Alaska 2008.
Yusuf Aytar, Mubarak Shah, and Jiebo
Luo, Utilizing Semantic Word Similarity
Measures for Video Retrieval, IEEE
Conference on Computer Vision and Pattern Recognition, Anchorage, Alaska
2008.
Arslan Basharat, Alexei Gritai, and Mubarak Shah, Learning Object Motion
Patterns for Anomaly Detection and
Improved Object Detection, IEEE Conference on Computer Vision and Pattern
Recognition, Anchorage, Alaska 2008.
Andrew Miller, Mubarak Shah, and Don
Harper, Landing a UAV on a Runway
Using Image Registration, International
Conference on Robotics & Automation,
2008.
Jun Xie, Shahid Khan, and Mubarak
Shah, Automatic Tracking of Escherichia Coli Bacteria, 11th International Conference on Medical Image Computing
and Computer Assisted Intervention,
MICCAI, September 6-10, New York
City. 2008.
Saad Ali and Mubarak Shah, Floor
Fields for Tracking in High Density
Crowded Scenes, European Conference
on Computer Vision, Marseille, France,
October 12-18, 2008.
Min Hu, Saad Ali, and Mubarak Shah,
Detecting Global Motion Patterns in
Complex Videos, International Conference on Pattern Recognition, December
2008.
Min Hu, Saad Ali and Mubarak Shah,
Learning Motion Patterns in Crowded
Scenes Using Motion Flow Field, International Conference on Pattern Recognition, December 2008.
Jun Xie, Min Hu, and Mubarak Shah,
Unfolding Warping for Object Recognition, International Conference on Pattern
Recognition, December 2008.
-6-
Ramin Mehran, Alexis Oyama and Mubarak Shah, Abnormal Crowd Behavior
Detection using Social Force Model,
IEEE Conference on Computer Vision
and Pattern Recognition, Miami, Florida,
2009.
Kishore Reddy, Jingen Liu, and Mubarak
Shah, Incremental Action Recognition
Using Feature-Tree, International Conference on Computer Vision, September
2009.
Arslan Basharat and Mubarak Shah,
Time Series Prediction by Chaotic Modeling of Nonlinear Dynamical Systems,
International Conference on Computer
Vision, September 2009.
Mikel Rodriguez, Saad Ali and Takeo
Kanade, Tracking in Unstructured
Crowded Scenes, International Conference on Computer Vision, September
2009.
Yang Yang, Jingen Liu, and Mubarak
Shah, Video Scene Understanding Using
Multi-scale Analysis, International Conference on Computer Vision, September
2009.
http://www.vision.eecs.ucf.edu/publications
INVITED TALKS (by Professor Shah)
JOURNALS
Arslan Basharat, Yun Zhai, Mubarak
Shah, Content Based Video Matching
Using Spatiotemporal Volumes, Computer Vision and Image Understanding,
Volume 110, Issue 3, June 2008, Pages
360-377.
J. Ahmed, M.N. Jafri, M.Shah, M. Akbar,
Real-time edge enhanced dynamic correlation and predictive open-loop carfollowing control for robust tracking,
Machine Vision and Applications (2008)
19:1-25.
Pingkun Yan, Xiaobo Zhou, Mubarak
Shah, and Stephen T.C. Wong, Automatic Segmentation of High Throughput
RNAi Fluorescent Cellular Images,
IEEE Trans. Information Technology in
Biomedicine, Volume 12, Number 1,
January 2008.
Jun Xie, Pheng-Ann Heng, and Mubarak
Shah, A Shape Matching Approach Using Skeletal Features and Context Descriptor, Pattern Recognition, Volume 41,
Issue 5, May 2008.
Yaser Sheikh, and Mubarak Shah, Trajectory Association Across Multiple Airborne Cameras, IEEE Transactions on
PAMI, Volume 30, No. 2, February
2008, Pages 361-367.
Omar Javed, Khurram Shafique, Zeeshan
Rasheed and Mubarak Shah, Modeling
intercamera spacetime and appearance
relationships for tracking across nonoverlapping views, Computer Vision and
Image Understanding, Volume 109, Issue
2, February 2008, Pages 146-162.
A. Yilmaz and M. Shah, A Differential
Geometric Approach To Representing
the Human Actions, Computer Vision
and Image Understanding Journal, Vol.
109 No. 3, pp.335-351 2008.
Pavel Babenko and Mubarak Shah,
MinGPU: A Minimum GPU Library for
Computer Vision, Journal of Real-Time
Processing, (2008) 3:255-268.
J. Xie, P.A. Heng and Mubarak Shah,
Image Diffusion Using Saliency Bilateral Filter, IEEE Transactions on Information Technology in Biomedicine, Volume 12, Number 6, 768-771, 2008.
Saad M. Khan and Mubarak Shah, Tracking Multiple Occluding People by Localizing on Multiple Scene Planes, IEEE
Transactions on Pattern Analysis and
Machine Intelligence, Volume: 31, Issue:
3, pp 505-519, March 2009.
Pingkun Yan, Ashraf A. Kassim, Weijia
Shen, and Mubarak Shah, Modeling Interaction for Segmentation of Neighboring Structures, IEEE Trans. on PAMI,
Volume 31, Number 3, pp 505-519,
March 2009.
I. Saleemi, K. Shafique, M.Shah, Probabilistic Modeling of Scene Dynamics for
Applications in VIsual Surveillance,
IEEE TPAMI 2008, Vol 31, No. 8, August 2009.
Jun Xie, Shahid Khan, and Mubarak
Shah, Automatic Tracking of Escherichia Coli in Phase-Contrast Microscopy
Video, IEEE Trans. on Biomedical Engineering, Vol. 56, no2, pp. 390-399, 2009.
Alexei Gritai, Yaser Sheikh, Cen Rao and
Mubarak Shah, Matching Trajectories of
Anatomical Landmarks under Viewpoint
Anthropometric, and Temporal Transforms, International Journal of Computer
Vision (IJCV), Volume 84, Issue 3, Pages: 325-343, September 2009.
-7-
Visual Analysis of Crowded Scenes, invited talk at DARPA Workshop on Cityscapes, Reno, Nevada, March 8-9, 2008.
Video Surveillance and Monitoring,
Klagenfurt University, Klagenfurt, Austria, July 15, 2008.
Human Action Recognition Using Bag
of Video Words, Vienna University of
Technology, Vienna, July 17, 2008.
Video Surveillance and Monitoring,
Austrian Research Centers GmbH, Vienna, August 1, 2008.
Tracking Across Multiple Moving Cameras, Missouri University of Science and
Technology, ACM Distinguished Lecture, Rolla, Missouri, October 10, 2008.
UCF VIRAT efforts, Audacity/VIRAT
workshop, Lockheed Martin, Herndon,
VA, February 18, 2009.
Taming Crowded Visual Scenes, ECE
department, Wayne State University,
Detroit, MI, April 7, 2009.
Taming Crowded Visual Scenes, EECS
department, University of Michigan Ann
Arbor, MI, April 8, 2009.
Taming Crowded Visual Scenes,
DARPA ISAT workshop, Berkeley, CA,
May 6, 2009.
Visual Analysis of Crowded Scenes, International Workshop on Video, Barcelona, Spain, May 27, 2009.
An Overview of Visual Tracking in EO
and IR Imagery, keynote talk, IEEE
Workshop on Object Tracking & Classification in and Beyond the Visible Spectrum (OTCBVS), CVPR 2009, Miami
Beach, FL, June 20, 2009.
Seminars
http://www.eecs.ucf.edu/index.php?id=research/seminars
Naresh Cuntoor
University of Maryland
Activity Modeling Using an SVD-like Decomposition
September 10, 2008
Amit Roy-Chowdhury
University of California, Riverside
From Single Images to Camera Networks: Modeling and Inference Strategies
September 15, 2008
Hierarchical Graph-based Representations for Segmentation,
Walter Kropatsch
Vienna University of Technol- Tracking and Shape Matching
ogy
December 3, 2008
Leandro Loss
University of Nevada, Reno
An Iterative Multi-Scale Tensor Voting Scheme for Perceptual
Grouping of Natural Shapes in Cluttered Backgrounds
December 5, 2008
Monique Thonnat
INRIA
Semantic Activity Recognition for Visual Surveillance and
Healthcare Monitoring
December 9, 2008
Jean-Marc Odobez
IDIAP Research Institute
Analysis of the Visual Focus of Attention in Group Conversation
December 12, 2008
Pingkun Yan
Philips Research
Segmentation of Prostate for Image Guided Targeted Biopsy
February 9, 2009
Dinesh Manocha
University of North Carolina
at Chapel Hill
Bringing Realism to Virtual Environments: Sounds and Crowds
February 11, 2009
Hanan Samet
University of Maryland
Sorting in Space
February 19, 2009
Jim Rehg
Georgia Tech
Towards a Theory of Cascaded Detectors
March 20, 2009
Arnold Smeulders
University of Amsterdam
Object Class Recognition
March 26, 2009
Donald Geman
Johns Hopkins University
Stationary Features and Cat Detection
March 30, 2009
Ronald Coifman
Yale University
Wavelets and Applications: Past and Future
April 14, 2009
Martial Hebert
Carnegie Mellon University
Some Steps in Modeling and Understanding in a User’s Environment from Vision Data
April 20, 2009
Bernhard Rinner
Klagenfurt University
Challenges and Opportunities of Distributed Smart Cameras
May 20, 2009
Computer Vision Lab
Electrical Engineering & Computer Science
University of Central Florida
4000 Central Florida Blvd.
Orlando, FL 32816-2362