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» Robust Principal Component Analysis for Computer Vision
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ECCV
2006
Springer
14 years 9 months ago
Learning Discriminative Canonical Correlations for Object Recognition with Image Sets
Abstract. We address the problem of comparing sets of images for object recognition, where the sets may represent arbitrary variations in an object's appearance due to changin...
Tae-Kyun Kim, Josef Kittler, Roberto Cipolla
ICCV
2009
IEEE
15 years 20 days ago
Detection of Human Actions From A Single Example
We present an algorithm for detecting human actions based upon a single given video example of such actions. The proposed method is unsupervised, does not require learning, segm...
Hae Jong Seo, Peyman Milanfar
CVPR
2003
IEEE
14 years 9 months ago
Video-Based Face Recognition Using Probabilistic Appearance Manifolds
This paper presents a novel method to model and recognize human faces in video sequences. Each registered person is represented by a low-dimensional appearance manifold in the amb...
Kuang-Chih Lee, Jeffrey Ho, Ming-Hsuan Yang, David...
CVPR
2008
IEEE
14 years 9 months ago
Where am I: Place instance and category recognition using spatial PACT
We introduce spatial PACT (Principal component Analysis of Census Transform histograms), a new representation for recognizing instances and categories of places or scenes. Both pl...
Jianxin Wu, James M. Rehg
ICCV
2003
IEEE
14 years 9 months ago
Images as Bags of Pixels
We propose modeling images and related visual objects as bags of pixels or sets of vectors. For instance, gray scale images are modeled as a collection or bag of (X, Y, I) pixel v...
Tony Jebara