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» A novel Bayesian shape model for facial feature extraction
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CVPR
2012
IEEE
11 years 10 months ago
Unsupervised learning of translation invariant occlusive components
We study unsupervised learning of occluding objects in images of visual scenes. The derived learning algorithm is based on a probabilistic generative model which parameterizes obj...
Zhenwen Dai, Jörg Lücke
ICMCS
2005
IEEE
246views Multimedia» more  ICMCS 2005»
14 years 1 months ago
A SOM-wavelet networks for face identification
This paper describes a novel SOM-Wavelet Networks method for face recognition. We employed a SOM algorithm, which is based on the structure of a biological model, to extract shape...
Yang Zhi, Gu Ming
DAS
2010
Springer
13 years 9 months ago
Overlapped text segmentation using Markov random field and aggregation
Separating machine printed text and handwriting from overlapping text is a challenging problem in the document analysis field and no reliable algorithms have been developed thus f...
Xujun Peng, Srirangaraj Setlur, Venu Govindaraju, ...
ICMCS
2006
IEEE
143views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Object Recognition and Recovery by Skeleton Graph Matching
This paper presents a robust and efficient skeleton-based graph matching method for object recognition and recovery applications. The novel feature is to unify both object recogni...
Lei He, Chia Y. Han, William G. Wee
MVA
2007
207views Computer Vision» more  MVA 2007»
13 years 9 months ago
View-invariant Human Action Recognition Based on Factorization and HMMs
of the fundamental challenges of human action recognition is accounting for the variability that arises during video capturing. For a specific action class, the 2D observations of...
Xi Li, Kazuhiro Fukui