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ICASSP
2010
IEEE
15 years 1 days ago
Supervised topic model for automatic image annotation
This paper presents a new probabilistic model for the task of image annotation. Our model, which we call sLDA-bin, extends supervised Latent Dirichlet Allocation (sLDA) model to h...
Duangmanee Putthividhya, Hagai Thomas Attias, Srik...
WACV
2005
IEEE
15 years 5 months ago
Using Co-Occurrence and Segmentation to Learn Feature-Based Object Models from Video
A number of recent systems for unsupervised featurebased learning of object models take advantage of cooccurrence: broadly, they search for clusters of discriminative features tha...
Thomas S. Stepleton, Tai Sing Lee
ICCV
2009
IEEE
16 years 4 months ago
TagProp: Discriminative Metric Learning in Nearest Neighbor Models for Image Auto-Annotation
Image auto-annotation is an important open problem in computer vision. For this task we propose TagProp, a discriminatively trained nearest neighbor model. Tags of test images a...
Matthieu Guillaumin, Thomas Mensink, Jakob Verbeek...
CVPR
2008
IEEE
15 years 6 months ago
A theoretical analysis of linear and multi-linear models of image appearance
Linear and multi-linear models of object shape/appearance (PCA, 3DMM, AAM/ASM, multilinear tensors) have been very popular in computer vision. In this paper, we analyze the validi...
Yilei Xu, Amit K. Roy Chowdhury
ICDM
2009
IEEE
156views Data Mining» more  ICDM 2009»
14 years 9 months ago
Scalable Classification in Large Scale Spatiotemporal Domains Applied to Voltage-Sensitive Dye Imaging
We present an approach for learning models that obtain accurate classification of large scale data objects, collected in spatiotemporal domains. The model generation is structured ...
Igor Vainer, Sarit Kraus, Gal A. Kaminka, Hamutal ...