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ECCV
2004
Springer
14 years 11 months ago
A Constrained Semi-supervised Learning Approach to Data Association
Data association (obtaining correspondences) is a ubiquitous problem in computer vision. It appears when matching image features across multiple images, matching image features to ...
Hendrik Kück, Nando de Freitas, Peter Carbone...
TCSV
2008
195views more  TCSV 2008»
13 years 9 months ago
Locality Versus Globality: Query-Driven Localized Linear Models for Facial Image Computing
Conventional subspace learning or recent feature extraction methods consider globality as the key criterion to design discriminative algorithms for image classification. We demonst...
Yun Fu, Zhu Li, Junsong Yuan, Ying Wu, Thomas S. H...
ICCV
2005
IEEE
14 years 2 months ago
Learning Hierarchical Models of Scenes, Objects, and Parts
We describe a hierarchical probabilistic model for the detection and recognition of objects in cluttered, natural scenes. The model is based on a set of parts which describe the e...
Erik B. Sudderth, Antonio B. Torralba, William T. ...
BMVC
2000
13 years 10 months ago
Probabilistic PCA and ICA Subspace Mixture Models for Image Segmentation
High-dimensional data, such as images represented as points in the space spanned by their pixel values, can often be described in a significantly smaller number of dimensions than...
Dick de Ridder, Josef Kittler, Robert P. W. Duin
ICMCS
2006
IEEE
139views Multimedia» more  ICMCS 2006»
14 years 3 months ago
Automatic Semantic Annotation of Images using Spatial Hidden Markov Model
This paper presents a new spatial-HMM(SHMM)for automatically classifying and annotating natural images. Our model is a 2D generalization of the traditional HMM in the sense that b...
Feiyang Yu, Horace Ho-Shing Ip