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ICML
2007
IEEE
16 years 20 days ago
Comparisons of sequence labeling algorithms and extensions
In this paper, we survey the current state-ofart models for structured learning problems, including Hidden Markov Model (HMM), Conditional Random Fields (CRF), Averaged Perceptron...
Nam Nguyen, Yunsong Guo
CVIU
2006
222views more  CVIU 2006»
14 years 12 months ago
Conditional models for contextual human motion recognition
We present algorithms for recognizing human motion in monocular video sequences, based on discriminative Conditional Random Field (CRF) and Maximum Entropy Markov Models (MEMM). E...
Cristian Sminchisescu, Atul Kanaujia, Dimitris N. ...
CVPR
2011
IEEE
14 years 7 months ago
Learning Context for Collective Activity Recognition
In this paper we present a framework for the recognition of collective human activities. A collective activity is defined or reinforced by the existence of coherent behavior of i...
Wongun Choi, Silvio Savarese, Khuram Shahid
ICIP
2010
IEEE
14 years 9 months ago
An automated vertebra identification and segmentation in CT images
In this paper, we propose a new 3D framework to identify and segment VBs and TBs in clinical computed tomography (CT) images without any user intervention. The Matched filter is e...
Melih S. Aslan, Asem M. Ali, Ham Rara, Aly A. Fara...
ICCV
2003
IEEE
16 years 1 months ago
A Multi-scale Generative Model for Animate Shapes and Parts
This paper presents a multi-scale generative model for representing animate shapes and extracting meaningful parts of objects. The model assumes that animate shapes (2D simple clo...
Aleksandr Dubinskiy, Song Chun Zhu