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NIPS
2008
13 years 9 months ago
Learning a discriminative hidden part model for human action recognition
We present a discriminative part-based approach for human action recognition from video sequences using motion features. Our model is based on the recently proposed hidden conditi...
Yang Wang 0003, Greg Mori
SSPR
2010
Springer
13 years 6 months ago
Information Theoretical Kernels for Generative Embeddings Based on Hidden Markov Models
Many approaches to learning classifiers for structured objects (e.g., shapes) use generative models in a Bayesian framework. However, state-of-the-art classifiers for vectorial d...
André F. T. Martins, Manuele Bicego, Vittor...
TSMC
2008
95views more  TSMC 2008»
13 years 7 months ago
Natural Movement Generation Using Hidden Markov Models and Principal Components
Recent studies have shown that the perception of natural movements--in the sense of being "humanlike"--depends on both joint and task space characteristics of the movemen...
Junghyun Kwon, Frank C. Park
ALMOB
2006
155views more  ALMOB 2006»
13 years 7 months ago
A phylogenetic generalized hidden Markov model for predicting alternatively spliced exons
Background: An important challenge in eukaryotic gene prediction is accurate identification of alternatively spliced exons. Functional transcripts can go undetected in gene expres...
Jonathan E. Allen, Steven L. Salzberg
CVIU
2006
222views more  CVIU 2006»
13 years 7 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. ...