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ICMCS
2009
IEEE
115views Multimedia» more  ICMCS 2009»
13 years 3 months ago
A framework to detect and classify activity transitions in low-power applications
Minimizing the number of computations a low-power device makes is important to achieve long battery life. In this paper we present a framework for a low-power device to minimize t...
Jeffrey Boyd, Hari Sundaram
ICPR
2006
IEEE
14 years 7 months ago
A Combined Bayesian Markovian Approach for Behaviour Recognition
Numerous techniques exist which can be used for the task of behavioural analysis and recognition. Common amongst these are Bayesian networks and Hidden Markov Models. Although the...
David Paul Young, James M. Ferryman, Nicholas L. C...
IJCAI
2007
13 years 7 months ago
A Hybridized Planner for Stochastic Domains
Markov Decision Processes are a powerful framework for planning under uncertainty, but current algorithms have difficulties scaling to large problems. We present a novel probabil...
Mausam, Piergiorgio Bertoli, Daniel S. Weld
ICML
2000
IEEE
14 years 6 months ago
Maximum Entropy Markov Models for Information Extraction and Segmentation
Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech t...
Andrew McCallum, Dayne Freitag, Fernando C. N. Per...
FGR
2000
IEEE
162views Biometrics» more  FGR 2000»
13 years 9 months ago
Person Tracking in Real-World Scenarios Using Statistical Methods
This paper presents a novel approach to robust and flexible person tracking using an algorithm that combines two powerful stochastic modeling techniques: The first one is the tech...
Gerhard Rigoll, Stefan Eickeler, Stefan Mülle...