Posts Tagged ‘recognition algorithms’

Tobii demo of an eye controlled natural user interface - March 24th, 2011

Involuntary Gesture Recognition for Predicting Cerebral Palsy in High-Risk Infants - July 21st, 2010

Moleskins and Pens

Photo courtesy of paulworthington

Congratulations to former Informatics visiting scholar Mohan Singh and Informatics Faculty Member Donald J. Patterson on having their paper accepted to the IEEE International Symposium on Wearable Computers
‘Involuntary Gesture Recognition for Predicting Cerebral Palsy in High-Risk Infants’

Abstract:In this paper we describe a system that leverages accelerometers to recognize a particular involuntary gesture in babies that have been born preterm. These gestures, known as cramped-synchronized general movements, have been shown to be highly correlated with a diagnosis of Cerebral Palsy. In order to test our system we recorded data from 10 babies admitted to the newborn intensive care unit at the UCI Medical Center. We applied machine learning techniques to features based on their data and were able to obtain high accuracies on this cohort. Validated video observation annotations were utilized as ground truth. Finally, we conducted an analysis to understand the basis of the algorithmic predictions.

Congratulations Mohan, and Don!

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Posted: 7/21/10 3:59 pm PDT by Comments Off
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Sensecam goes public for a mere $720.00 - May 28th, 2010



“Vicon Revue [] is the commercial reincarnation of Microsoft’s Sensecam concept: a wearable digital camera that is designed to take photographs passively, without user intervention, while it is being worn. Its purpose is to support life-loggers wanting to track and document their everyday movements as digital memories. In combination with other physical sensors or additional image-recognition algorithms, the potential opportunities are enormous.”

via information aesthetics

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Posted: 5/28/10 6:00 am PDT by Comments Off
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AAAI 2009 Spring Symposium on Human Behavior Modeling - August 5th, 2008

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“The AAAI 2009 Spring Symposium on Human Behavior Modeling will explore methods for creating models of individual and group behavior from data.
Models include generative and discriminative statistical models, relational models, and social network models
Data includes low-level sensor data (GPS, RFID, accelerometers, physiological measures, etc.), video, speech, and text
Behaviors include high-level descriptions of purposeful and meaningful activity or abstractions of cognitive and affective states. These include activities of daily living (e.g., preparing a meal), interaction between small sets of individuals (e.g., having a conversation), mass behavior of groups (e.g. the flow of traffic in a city) and related internal user states.

While behavior modeling is part of many research communities, such as intelligent user interfaces, machine vision, smart homes for aging in place, discourse understanding, social network analysis, and others, this workshop will be distinguished by its emphasis on exploring general representations and reasoning methods that can apply across many different domains.”

More info on papers, panels, and doctoral thesis position papers can be found here and here.

Important dates

October 3, 2008: Papers and doctoral thesis position papers due
November 7, 2008: Notifications of acceptances mailed out
January 14, 2009: Camera ready paper due
January 31, 2009: Intention to participate for those not contributing a paper
February 27, 2009: Registration deadline
March 23-25, 2009: Spring Symposium Series, Stanford University

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Posted: 8/5/08 11:25 am PDT by Comments Off
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