Paper in Advanced Robotics (2009): “Human Action Recognition Using Global Point Feature Histograms and Action Shapes”

October 29th, 2009 Irfan Essa Posted in Activity Recognition, Franzi Meier, Intelligent Environments, Michael Beetz, Papers No Comments »

Radu Bogdan Rusu, Jan Bandouch, Franziska Meier, Irfan Essa and Michael Beetz (2009) “Human Action Recognition Using Global Point Feature Histograms and Action Shapes”, in Journal of Advanced Robotics, volume 23, pages 1873–1908, Koninklijke Brill NV, Leiden and The Robotics Society of Japan, 2009. [ DOI | PDF]

Abstract

This paper investigates the recognition of human actions from three-dimensional (3-D) point clouds that encode the motions of people acting in sensor-distributed indoor environments. Data streams are time sequences of silhouettes extracted from cameras in the environment. From the 2-D silhouette contours we generate space–time streams by continuously aligning and stacking the contours along the time axis as third spatial dimension. The space–time stream of an observation sequence is segmented into parts corresponding to subactions using a pattern matching technique based on suffix trees and interval scheduling. Then, the segmented space–time shapes are processed by treating the shapes as 3-D point clouds and estimating global point feature histograms for them. The resultant models are clustered using statistical analysis and our experimental results indicate that the presented methods robustly derive different action classes. This holds despite large intra-class variance in the recorded datasets due to performances from different persons at different time intervals.

© Koninklijke Brill NV, Leiden and The Robotics Society of Japan, 2009

Overview of the approach.

Overview of the approach.

Keywords: Action recognition, point cloud, global features, action segmentation

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GT Research Horizons — Fall 2003

October 30th, 2003 Irfan Essa Posted in Aware Home, Health Systems, Human Factors, In The News, Intelligent Environments, Research No Comments »

GT Research Horizons — Fall 2003

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

September 29th, 2002 Irfan Essa Posted in AAAI/IJCAI/UAI, Activity Recognition, Darnell Moore, Intelligent Environments, Papers No Comments »

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

Recognizing Black Jack

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NY Times Article (2001): “Smart Home, to Avoid the Nursing Home”

April 5th, 2001 Irfan Essa Posted in Aware Home, In The News, Intelligent Environments, Research No Comments »

Anne Eisenberg (2001)“A ‘Smart’ Home, to Avoid the Nursing Home” New York Times Circuits Section,

April 5, 2001 Issue

Quote from the Article: “Cameras are going to rule one day at the Georgia Tech house, though, staff members there say. Dr. Irfan A. Essa, a computer science professor at Georgia Tech, is one of the people building a tracking system, based on video cameras, that will one day replace radio frequency tags. ”We can locate where the person is,” Dr. Essa said, ”and make a first-level guess at where this person is heading using the optical sensors.””

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Paper: IEEE Personal Commications (2000) “Ubiquitous sensing for smart and aware environments”

October 14th, 2000 Irfan Essa Posted in Aware Home, Intelligent Environments, Papers, Research No Comments »


Essa, I.A (2000), “Ubiquitous sensing for smart and aware environments” In Personal Communications, IEEE [see also IEEE Wireless Communications] Publication Date: Oct. 2000, Volume: 7 , Issue: 5
On page(s): 47 – 49, ISSN: 1070-9916, CODEN: IPCME7, INSPEC Accession Number:6756447, Digital Object Identifier: 10.1109/98.878538

Abstract

As computing technology continues to become increasingly pervasive and ubiquitous, we envision the development of environments that can sense what we are doing and support our daily activities. In this article, we outline our efforts toward building such environments and discuss the importance of a sensing and signal-understanding infrastructure that leads to awareness of what is happening in an environment and how it can best be supported. Such an infrastructure supports both high- and low-end data transmission and processing, while allowing for detailed interpretation, modeling and recognition from sensed information. We are currently prototyping several aware environments to aid in the development and study of such sensing and computation in real-world settings

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