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CDC
2008
IEEE
157views Control Systems» more  CDC 2008»
13 years 5 months ago
A hidden Markov filtering approach to multiple change-point models
We describe a hidden Markov modeling approach to multiple change-points that has attractive computational and statistical properties. This approach yields explicit recursive filter...
Tze Leung Lai, Haipeng Xing
ECCV
2008
Springer
14 years 6 months ago
A Probabilistic Approach to Integrating Multiple Cues in Visual Tracking
Abstract. This paper presents a novel probabilistic approach to integrating multiple cues in visual tracking. We perform tracking in different cues by interacting processes. Each p...
Wei Du, Justus H. Piater
PRL
2006
191views more  PRL 2006»
13 years 4 months ago
Applications of hidden Markov models in bar code decoding
We present a novel approach to edge detection in bar code signals using a hidden Markov model (HMM). We also present an algorithm for selection of an optimal filter scale used in ...
S. Kresic-Juric, D. Madej, Fadil Santosa
CVIU
2004
132views more  CVIU 2004»
13 years 4 months ago
Layered representations for learning and inferring office activity from multiple sensory channels
We present the use of layered probabilistic representations for modeling human activities, and describe how we use the representation to do sensing, learning, and inference at mul...
Nuria Oliver, Ashutosh Garg, Eric Horvitz
ICASSP
2011
IEEE
12 years 8 months ago
A non-negative approach to semi-supervised separation of speech from noise with the use of temporal dynamics
We present a semi-supervised source separation methodology to denoise speech by modeling speech as one source and noise as the other source. We model speech using the recently pro...
Gautham J. Mysore, Paris Smaragdis