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» A Topic-Motion Model for Unsupervised Video Object Discovery
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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
ICVGIP
2004
15 years 1 months ago
Learning Layered Pictorial Structures from Video
We propose a new unsupervised learning method to obtain a layered pictorial structure (LPS) representation of an articulated object from video sequences. It will be seen that this...
M. Pawan Kumar, Philip H. S. Torr, Andrew Zisserma...
CVPR
2008
IEEE
16 years 1 months ago
Decomposition, discovery and detection of visual categories using topic models
We present a novel method for the discovery and detection of visual object categories based on decompositions using topic models. The approach is capable of learning a compact and...
Mario Fritz, Bernt Schiele
MVA
2007
160views Computer Vision» more  MVA 2007»
15 years 1 months ago
Probabilistic Motion Segmentation of Videos for Temporal Super Resolution
A novel scheme is proposed for achieving motion segmentation in low-frame rate videos, with application to temporal super resolution. Probabilistic generative models are commonly ...
Arasanathan Thayananthan, Masahiro Iwasaki, Robert...
CVPR
2000
IEEE
16 years 1 months ago
Towards Automatic Discovery of Object Categories
We propose a method to learn heterogeneous models of object classes for visual recognition. The training images contain a preponderance of clutter and learning is unsupervised. Ou...
Markus Weber, Max Welling, Pietro Perona