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» Selecting relevant features for human motion recognition
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NIPS
2001
13 years 9 months ago
Unsupervised Learning of Human Motion Models
This paper presents an unsupervised learning algorithm that can derive the probabilistic dependence structure of parts of an object (a moving human body in our examples) automatic...
Yang Song, Luis Goncalves, Pietro Perona
ICB
2009
Springer
141views Biometrics» more  ICB 2009»
14 years 2 months ago
Towards Structured Approaches to Arbitrary Data Selection and Performance Prediction for Speaker Recognition
We developed measures relating feature vector distributions to speaker recognition (SR) performances for performance prediction and potential arbitrary data selection for SR. We ex...
Howard Lei
CVPR
2009
IEEE
13 years 11 months ago
Switching Gaussian Process Dynamic Models for simultaneous composite motion tracking and recognition
Traditional dynamical systems used for motion tracking cannot effectively handle high dimensionality of the motion states and composite dynamics. In this paper, to address both is...
Jixu Chen, Minyoung Kim, Yu Wang, Qiang Ji
PR
2007
148views more  PR 2007»
13 years 7 months ago
Learning the best subset of local features for face recognition
We propose a novel, local feature-based face representation method based on twostage subset selection where the first stage finds the informative regions and the second stage ...
Berk Gökberk, M. Okan Irfanoglu, Lale Akarun,...
IPSN
2010
Springer
13 years 9 months ago
Collaborative signal processing for action recognition in body sensor networks: a distributed classification algorithm using mot
Body sensor networks are emerging as a promising platform for remote human monitoring. With the aim of extracting bio-kinematic parameters from distributed body-worn sensors, thes...
Hassan Ghasemzadeh, Vitali Loseu, Roozbeh Jafari