My teaching activities for Spring 2016 are CS 4475 / 6475 Computational Photography (On-Campus, in Atlanta), Tue-Thu 1:35 pm-2:55 pm, KACB 2443, supported by TAs, Unaiza Ahsan, Huda Alamri, Amit Agarwal, and Palal Shastri. CS 6475 Computational Photography (Part of the Online MS CS Program), supported by TAs, Daniel Castro, Kim Sirichoke, Vickie Backman, Brandon Guttersohn, Isabel Lupiani […]
Paper Abstract We present an automated framework for a visual assessment of the expertise level of surgeons using the OSATS (Objective Structured Assessment of Technical Skills) criteria. Video analysis technique for extracting motion quality via frequency coefficients is introduced. The framework is tested in a case study that involved analysis of videos of medical students with different expertise levels performing basic […]
Presentation at Max-Planck-Institut für Informatik in Saarbrücken (2015): "Video Analysis and Enhancement"
Video Analysis and Enhancement: Spatio-Temporal Methods for Extracting Content from Videos and Enhancing Video Output Irfan Essa (prof.irfanessa.com) Georgia Institute of Technology School of Interactive Computing Hosted by Max-Planck-Institut für Informatik in Saarbrucken (Bernt Schiele, Director of Computer Vision and Multimodal Computing) Abstract In this talk, I will start with describing the pervasiveness of image and video content, […]
Dagstuhl Workshop 2015: "Modeling and Simulation of Sport Games, Sport Movements, and Adaptations to Training"
Participated in the Dagstuhl Workshop on “Modeling and Simulation of Sport Games, Sport Movements, and Adaptations to Training” at the Dagstuhl Castle, September 13 – 16, 2015. Motivation Computational modeling and simulation are essential to analyze human motion and interaction in sports science. Applications range from game analysis, issues in training science like training load-adaptation […]
Presentation at Max-Planck-Institute for Intelligent Systems in Tübingen (2015): "Data-Driven Methods for Video Analysis and Enhancement"
Data-Driven Methods for Video Analysis and Enhancement Irfan Essa (prof.irfanessa.com) Georgia Institute of Technology Thursday, September 10, 2 pm, Max Planck House Lecture Hall (Spemannstr. 36) Hosted by Max-Planck-Institute for Intelligent Systems (Michael Black, Director of Percieving Systems) Abstract In this talk, I will start with describing the pervasiveness of image and video content, and how such […]
Paper Abstract We present a method to analyze images taken from a passive egocentric wearable camera along with the contextual information, such as time and day of a week, to learn and predict everyday activities of an individual. We collected a dataset of 40,103 egocentric images over a 6 month period with 19 activity classes […]
In fall 2015 fall term, I am teaching two classes. Both for the Georgia Tech’s Online MSCS program. CS 6475: Computational Photography CS 6476: Computer Vision (This class was originally developed and offered by Aaron Bobick, but as he is now a Dean at Washington University, St. Louis, I have taken over as Instructor.
I was invited to participate and present at the King Abdullah University of Science & Technology Conference on Computational Imaging and Vision (CIV) March 1-4, 2015 Building 19 Level 3, Lecture Halls Visual Computing Center (VCC) Invited Speakers included Shree Nayar – Columbia University Daniel Cremers – Technical University of Munich Rene Vidal –The Johns […]
Paper Abstract Most of the approaches for indoor RGBD semantic labeling focus on using pixels or superpixels to train a classifier. In this paper, we implement a higher level segmentation using a hierarchy of superpixels to obtain a better segmentation for training our classifier. By focusing on meaningful segments that conform more directly to objects, […]
Citation Abstract We present an algorithm for finding temporally consistent occlusion boundaries in videos to support the segmentation of dynamic scenes. We learn occlusion boundaries in a pairwise Markov random field (MRF) framework. We first estimate the probability of a spatiotemporal edge being an occlusion boundary by using appearance, flow, and geometric features. Next, we […]