Irfan Essa's Academic Activities » AI

Event: AAAI 2008 Special Track on Physically-Grounded AI

Irfan Essa — Thu, 14 Feb 2008 22:19:01 +0000

I am Co-Chairing with Drew Bagnell (CMU), Wolfram Burgard (University of Frieberg) a Special Track on Physically-Grounded AI. See AAAI-08: Twenty-Third Conference on Artificial Intelligence, Chicago, IL, USA. The goal of this special track is to bring researhers from computer vision, robotics, machine learning and activity recognition to AAAI in a unified forum. All papers in this track will be full AAAI papers.

We received around 60 submissions to this track and expect a few NECTAR (new scientific and technical advances in research) submissions too (DUE Feb 18, 2008). The primary track submissions are in process of review).

Abstract Submission Deadline: January 25, 2008 *DONE*
Paper Submission Deadline: January 30, 2008 *DONE*
Author Notification Deadline: April 1, 2008

Paper AAAI (2002): “Recognizing Multitasked Activities from Video using Stochastic Context-Free Grammar”

Irfan Essa — Sun, 29 Sep 2002 15:13:50 +0000

D. Moore and I. Essa (2002). “Recognizing multitasked activities from video using stochastic context-free grammar”, in Proceedings of AAAI 2002. [PDF | Project Site]

Abstract

In this paper, we present techniques for recognizing com- plex, multitasked activities from video. Visual information like image features and motion appearances, combined with domain-specific information, like object context is used ini- tially to label events. Each action event is represented with a unique symbol, allowing for a sequence of interactions to be described as an ordered symbolic string. Then, a model of stochastic context-free grammar (SCFG), which is devel- oped using underlying rules of an activity, is used to provide the structure for recognizing semantically meaningful behav- ior over extended periods. Symbolic strings are parsed us- ing the Earley-Stolcke algorithm to determine the most likely semantic derivation for recognition. Parsing substrings al- lows us to recognize patterns that describe high-level, com- plex events taking place over segments of the video sequence. We introduce new parsing strategies to enable error detection and recovery in stochastic context-free grammar and meth- ods of quantifying group and individual behavior in activities with separable roles. We show through experiments, with a popular card game, the recognition of high-level narratives of multi-player games and the identification of player strate- gies and behavior using computer vision.

Recognizing Black Jack

Paper: AI Magazine (1999) “Computers Seeing People”

Irfan Essa — Wed, 14 Jul 1999 23:56:51 +0000

Irfan A. Essa “Computers Seeing People”, AI Magazine 20(2): Summer 1999, 69-82

Abstract

AI researchers are interested in building intelligent machines that can interact with them as they interact with each other. Science fiction writers have given us these goals in the form of HAL in 2001: A Space Odyssey and Commander Data in Star Trek: The Next Generation. However, at present, our computers are deaf, dumb, and blind, almost unaware of the environment they are in and of the user who interacts with them. In this article, I present the current state of the art in machines that can see people, recognize them, determine their gaze, understand their facial expressions and hand gestures, and interpret their activities. I believe that by building machines with such abilities for perceiving, people will take us one step closer to building HAL and Commander Data.