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» A probabilistic model for classifying segmented images
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CVPR
2011
IEEE
14 years 1 months ago
Nonlinear Shape Manifolds as Shape Priors in Level Set Segmentation and Tracking
We propose a novel nonlinear, probabilistic and variational method for adding shape information to level setbased segmentation and tracking. Unlike previous work, we represent sha...
Victor Prisacariu, Ian Reid
SIBGRAPI
2008
IEEE
15 years 4 months ago
Crop Type Recognition Based on Hidden Markov Models of Plant Phenology
This work introduces a Hidden Markov Model (HMM) based technique to classify agricultural crops. The method recognizes different crops by analyzing their spectral profiles over a ...
P. B. C. Leite, Raul Queiroz Feitosa, A. R. Formag...
3DOR
2008
15 years 4 days ago
Markov Random Fields for Improving 3D Mesh Analysis and Segmentation
Mesh analysis and clustering have became important issues in order to improve the efficiency of common processing operations like compression, watermarking or simplification. In t...
Guillaume Lavoué, Christian Wolf
ICMCS
1999
IEEE
202views Multimedia» more  ICMCS 1999»
15 years 2 months ago
Face Detection in Color Images Using Wavelet Packet Analysis
In this paper, we propose a novel scheme for automatic and fast detection of human faces in color images where the number, the location, the orientation and the size of the faces ...
Christophe Garcia, G. Zikos, George Tziritas
ICIP
2001
IEEE
15 years 11 months ago
Region-based approach for discriminant snakes
This paper proposes a statistic framework for segmenting textured areas over real images by discriminant snakes. Our active contour model has the ability to learn different textur...
Jordi Vitrià, Petia Radeva