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» Experimental Evaluation of Hierarchical Hidden Markov Models
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AMI
2009
Springer
15 years 4 months ago
Sensor-Based Human Activity Recognition in a Multi-user Scenario
Existing work on sensor-based activity recognition focuses mainly on single-user activities. However, in real life, activities are often performed by multiple users involving inter...
Liang Wang, Tao Gu, XianPing Tao, Jian Lu
97
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CVPR
2006
IEEE
16 years 4 months ago
Hidden Conditional Random Fields for Gesture Recognition
We introduce a discriminative hidden-state approach for the recognition of human gestures. Gesture sequences often have a complex underlying structure, and models that can incorpo...
Sy Bor Wang, Ariadna Quattoni, Louis-Philippe More...
ECCV
2010
Springer
15 years 7 months ago
Learning What and How of Contextual Models for Scene Labeling
We present a data-driven approach to predict the importance of edges and construct a Markov network for image analysis based on statistical models of global and local image feature...
ICASSP
2010
IEEE
15 years 2 months ago
Model-level data-driven sub-units for signs in videos of continuous Sign Language
We investigate the issue of sign language automatic phonetic subunit modeling, that is completely data driven and without any prior phonetic information. A first step of visual p...
Stavros Theodorakis, Vassilis Pitsikalis, Petros M...
ICASSP
2011
IEEE
14 years 5 months ago
Subspace pursuit method for kernel-log-linear models
This paper presents a novel method for reducing the dimensionality of kernel spaces. Recently, to maintain the convexity of training, loglinear models without mixtures have been u...
Yotaro Kubo, Simon Wiesler, Ralf Schlüter, He...