Announcement from Georgia Tech’s College of Computing about a new Interdisciplinary Research Center for Machine Learning (ML@GT) that I will be serving as the Inaugural Director. Machine Learning @ Georgia Tech Based in the College of Computing, ML@GT represents all of Georgia Tech. It is tasked with pushing forward the ability for computers to learn […]
Paper [bibtex file=IrfanEssaWS.bib key=2015-Zia-AASSUFA] 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 […]
Irfan EssaGeorgia 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 Perceiving Systems) Abstract In this talk, I will start with describing the pervasiveness of image and video content, and how such content is growing with the ubiquity of cameras. I will use […]
Paper Abstract Recognizing when eating activities take place is one of the key challenges in automated food intake monitoring. Despite progress over the years, most proposed approaches have been largely impractical for everyday usage, requiring multiple onbody sensors or specialized devices such as neck collars for swallow detection. In this paper, we describe the implementation […]
Paper Abstract We present a method to analyze images taken from a passive egocentric wearable camera along with contextual information, such as time and day of the week, to learn and predict the everyday activities of an individual. We collected a dataset of 40,103 egocentric images over 6 months with 19 activity classes and demonstrate […]
Citation Abstract Dietary self-monitoring has been shown to be an effective method for weight loss, but it remains an onerous task despite recent advances in food journaling systems. Semi-automated food journaling can reduce the effort of logging but often requires that eating activities be detected automatically. In this work, we describe results from a feasibility […]
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 […]
Sentiment analysis predicts the presence of positive or negative emotions in a text document. In this paper we consider higher-dimensional extensions of the sentiment concept, which represent a richer set of human emotions. Our approach goes beyond previous work in that our model contains a continuous manifold rather than a finite set of human emotions.
At ACM sponsored, 14th International Conference on Ubiquitous Computing (Ubicomp 2012), Pittsburgh, PA, September 5 – 7, 2012. Here are the highlights of my group’s participation in Ubicomp 2012. [bibtex key= 2012-Thomaz-RWAHTIS] (Oral Presentation at 2pm on Wednesday September 5, 2012) [bibtex key= 2012-Wang-OASUMC] (Oral Presentation at 2pm on Thursday September 6, 2012). In addition, my colleague, […]
Detecting Regions of Interest in Dynamic Scenes with Camera Motions Abstract We present a method to detect the regions of interests in moving camera views of dynamic scenes with multiple mov- ing objects. We start by extracting a global motion tendency that reflects the scene context by tracking movements of objects in the scene. We […]