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CVPR
2009
IEEE
15 years 2 months ago
Max-Margin Hidden Conditional Random Fields for Human Action Recognition
We present a new method for classification with structured latent variables. Our model is formulated using the max-margin formalism in the discriminative learning literature. We...
Yang Wang 0003, Greg Mori
ICMCS
2007
IEEE
151views Multimedia» more  ICMCS 2007»
14 years 2 months ago
Exploring Contextual Information in a Layered Framework for Group Action Recognition
Contextual information is important for sequence modeling. Hidden Markov Models (HMMs) and extensions, which have been widely used for sequence modeling, make simplifying, often u...
Dong Zhang, Samy Bengio
ICPR
2006
IEEE
14 years 1 months ago
HMM-based Human Action Recognition Using Multiview Image Sequences
In this paper, we present a novel method for human action recognition from any arbitrary view image sequence that uses the Cartesian component of optical flow velocity and human ...
Mohiuddin Ahmad, Seong-Whan Lee
IVC
2002
148views more  IVC 2002»
13 years 7 months ago
Detecting lameness using 'Re-sampling Condensation' and 'multi-stream cyclic hidden Markov models'
A system for the tracking and classification of livestock movements is presented. The combined `tracker-classifier' scheme is based on a variant of Isard and Blakes `Condensa...
Derek R. Magee, Roger D. Boyle
ICIP
2002
IEEE
14 years 21 days ago
Panoramic capturing and recognition of human activity
This paper presents a unified approach to human activity capturing and recognition. It targets applications such as a speaker walking, turning around, sitting and getting up from ...
Xinding Sun, B. S. Manjunath