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ECCV
2000
Springer
14 years 8 months ago
A Physically-Based Statistical Deformable Model for Brain Image Analysis
A probabilistic deformable model for the representation of brain structures is described. The statistically learned deformable model represents the relative location of head (skull...
Christophoros Nikou, Fabrice Heitz, Jean-Paul Arms...
ECCV
2004
Springer
14 years 8 months ago
A Statistical Model for General Contextual Object Recognition
We consider object recognition as the process of attaching meaningful labels to specific regions of an image, and propose a model that learns spatial relationships between objects....
Peter Carbonetto, Nando de Freitas, Kobus Barnard
CLOR
2006
13 years 10 months ago
A Sparse Object Category Model for Efficient Learning and Complete Recognition
We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a weakly-supervised manner: the model is learnt from examp...
Robert Fergus, Pietro Perona, Andrew Zisserman
ICPR
2000
IEEE
13 years 11 months ago
Probabilistic Saliency Approach for Elongated Structure Detection Using Deformable Models
In this paper we address the object recognition problem in a probabilistic framework to detect and describe object appearance through image features organized by means of active c...
Xavier Orriols, Ricardo Toledo, Xavier Binefa, Pet...
ICIP
2005
IEEE
14 years 11 days ago
HMM-based motion recognition system using segmented PCA
In this paper, we propose a novel technique for modelbased recognition of complex object motion trajectories using Hidden Markov Models (HMM). We build our models on Principal Com...
Faisal I. Bashir, Wei Qu, Ashfaq A. Khokhar, Dan S...