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, […]
Video Stabilization and Rolling Shutter Removal on YouTube Abstract In this talk, I will over a variety of approaches my group is working on for video analysis and enhancement. In particular, I will describe our approach for a video stabilizer (currently implemented on YouTube) and its extensions. This work is in collaboration with Matthias Grundmann […]
At IEEE CVPR 2012 is in Providence RI, from Jun 16 – 21, 2012. Busy week ahead meeting good friends and colleagues. Here are some highlights of what my group is involved with. Paper in Main Conference K. Kim, D. Lee, and I. Essa (2012), “Detecting Regions of Interest in Dynamic Scenes with Camera Motions,” in […]
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 […]
Extracting Content and Context from Video. (Presentation at CVPR 2012 workshop on Large Scale Video Search and Mining 2012, June 21, 2012)Irfan EssaGEORGIA Tech Abstract In this talk, I will describe various efforts aimed at extracting context and content from video. I will highlight some of our recent work in extracting spatio-temporal features and the […]
Videos Understanding: Extracting Content and Context from Video. (Presentation at the International Workshop on Computer Vision 2012, Ortigia, Siracusa, Sicily, May 22-24, 2012.) Irfan Essa GEORGIA Tech Abstract In this talk, I will describe various efforts aimed at extracting context and content from video. I will highlight some of our recent work in extracting spatio-temporal features […]
Our following paper was just awarded the Excellent Paper for 2011 in Computer Vision by Google Research. Casually shot videos captured by handheld or mobile cameras suffer from significant amount of shake. Existing in-camera stabilization methods dampen high-frequency jitter but do not suppress low-frequency movements and bounces, such as those observed in videos captured by […]
Paper/Citation Abstract Analysis and Recognition of motions and activities of objects in videos requires effective representations for analysis and matching of motion trajectories. In this paper, we introduce a new representation specifically aimed at matching motion trajectories. We model a trajectory as a continuous dense flow field from a sparse set of vector sequences using […]
Our work, as described in the following paper, now showcased in youtube. [bibtex file=IrfanEssaWS.bib key=2011-Grundmann-AVSWROCP] YouTube effects: Shake it like an Instagram picture via YouTube effects: Shake it like an Instagram picture — Online Video News. YouTube users can now apply a number of Instagram-like effects to their videos, giving them a cartoonish or Lomo-like look with […]
EAGER: Linguistic Task Transfer for Humans and Cyber Systems (Mike Stillman, Irfan Essa) NSF/RI This project, investigating formal languages as a general methodology for task transfer between distinct cyber-physical systems such as humans and robots, aims to expand the science of cyber physical systems by developing Motion Grammars that will enable task transfer between distinct […]