Oct 2013. PNNL Parking Lot 2 dataset as well as the tracking groundtruth are released.
Oct 2013. Code for CVPR13 paper is released.
Oct 2013. GMCP tracking code is being updated.
ALADDIN:Automated Low-Level Analysis and Description of Diverse Intelligence Video
The Automated Low-Level Analysis and Description of Diverse Intelligence Video (ALADDIN)
Program seeks to combine the state-of-the-art in video extraction, audio extraction, knowledge representation,
and search technologies in a revolutionary way to create a fast, accurate, robust,
and extensible technology that supports the multimedia analytic needs of the future.
UCF is a part of SRI-Sarnoff team and I've been leading UCF team
since summer 2012. I have investigated the benefits of using
concepts,attribute and objects in representating a video. I am also interested in
problem of event detection using only few examplars.
Evaluation of Tracking Algorithms on ISIS Video Data for the Wide Area Surveillance Project:
The project is a part of the Wide-Area Surveillance (WAS) project
being implemented by the U.S. Department of Homeland Security (DHS)
Science and Technology Directorate (S&T).
This project targets the development and evaluation of desirable
crowd tracking algorithm to be used in the (ISIS) context.
ISIS is a camera system developed by Massachusetts Institute of
Technology/Lincoln Laboratories (MIT/LL) and managed by Pacific
Northwest National Laboratory (PNNL).
The ISIS consists of a 100 Mpixel sensor (an array of image servers
and associated hard drive storage array).
While the ISIS camera can collect a large volume of video data for a
wide area monitored,
it demands an effective crowd tracking algorithm to be integrated
with the ISIS software system supporting video viewing and analysis.[More Info]
The first method that we proposed was a part-based greedy approach
detecting occluded part of a person and was published in CVPR2012.The
second approach was based on a global data association method which we
and introduced Generalized Minimum Clique Graph to efficiently track
in video sequences provided. The later was published in ECCV2012.
Improving Semantic Concept Detection through the Dictionary of Visually-distinct Elements Afshin Dehghan, Haroon Idrees and Mubarak Shah in Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition (CVPR 2014)
[Send Email for Code and Dataset]
Who Do I Look Like? Determining Parent-Offspring Resemblance via Gated Autoencoders Afshin Dehghan, Enrique G. Ortiz, Ruben Vilegas and Mubarak Shah in Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition (CVPR 2014)
[Send Email for Code and Dataset]
Complex Event Recognition by Latent Temporal Models of Concepts
Ehsan Zare Borzeshi,Afshin Dehghan, Massimo Piccardi, and Mubarak Shah in Proceedings of IEEE International Conference on Image Processing (ICIP 2014)
Visual Business Recognition - A Multimodal Approach
Amir Roshan Zamir, Afshin Dehghan and Mubarak Shah In Proceeding of ACM International Conference on Multimedia (ACM MM'2013)
Improving an Object Detector and Extracting Regions using Superpixels
Guang Shu, Afshin Dehghan and Mubarak Shah In proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR'13)
GMCP-Tracker: Global Multi-object Tracking Using Generalized Minimum Clique Graphs
Amir Roshan Zamir, Afshin Dehghan and Mubarak Shah In proceedings of European Conference on Computer Vision 2012 (ECCV'12)
Keynote: Automatic Detection and Tracking of Pedestrians in Videos with Various Crowd Densities Afshin Dehghan, Haroon Idrees, Amir Roshan Zamir and Mubarak Shah In Proceedings of PED, June 2012
Part-based Multiple-Person Tracking with Partial Occlusion Handling
Guang Shu, Afshin Dehghan, Omar Oreifej, Emily Hand, Mubarak Shah In proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR'12)
SRI-Sarnoff AURORA System at TRECVID 2012 Multimedia Event Detection and Recounting
H. Cheng, J. Liu, S. Ali, O. Javed, Q. Yu,A. Tamrakar, A. Divakaran†, H. S. Sawhney, R. Manmatha, Ja. Allan, A. Hauptmann, M. Shah, S. Bhattacharya, A. Dehghan , G. Friedland, B. M. Elizalde, T. Darrell, M. Witbrock, J. Curtis,
In Proceeding of Trecvid Video Retrieval Evaluation Workshop, NIST, Gaitherburg, Md, November 2012
A Multi-Agent Architecture for Tracking User Interactions in Browser-based Games
A.A. Bagherzadeh, S. Rezvankhah, S. Farahi, K. Khalvati, P. Mousavi, A. Dehghan, B. Ghaderi, L. Kashani, H. Moradi In proceedings of IEEE International Conference On Digital Game And Intelligent Toy Enhanced Learning (DIGITEL12)