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ICML
2001
IEEE
14 years 8 months ago
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
We present conditional random fields, a framework for building probabilistic models to segment and label sequence data. Conditional random fields offer several advantages over hid...
John D. Lafferty, Andrew McCallum, Fernando C. N. ...
ICASSP
2008
IEEE
14 years 2 months ago
Distributed multi-dimensional hidden Markov models for image and trajectory-based video classifications
In this paper, we propose a novel multi-dimensional distributed hidden Markov model (DHMM) framework. We first extend the theory of 2D hidden Markov models (HMMs) to arbitrary ca...
Xiang Ma, Dan Schonfeld, Ashfaq A. Khokhar
ICIP
2006
IEEE
14 years 9 months ago
Submotions for Hidden Markov Model Based Dynamic Facial Action Recognition
Video based analysis of a persons' mood or behavior is in general performed by interpreting various features observed on the body. Facial actions, such as speaking, yawning o...
Dejan Arsic, Joachim Schenk, Björn Schuller, ...
ICASSP
2008
IEEE
14 years 2 months ago
Joint tracking and video registration by factorial Hidden Markov models
Tracking moving objects from image sequences obtained by a moving camera is a difficult problem since there exists apparent motion of the static background. It becomes more dif...
Xue Mei, Fatih Murat Porikli
ICCV
2007
IEEE
14 years 9 months ago
Embedded Profile Hidden Markov Models for Shape Analysis
An ideal shape model should be both invariant to global transformations and robust to local distortions. In this paper we present a new shape modeling framework that achieves both...
Rui Huang, Vladimir Pavlovic, Dimitris N. Metaxas