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» Learning Statistical Structure for Object Detection
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CVPR
2007
IEEE
14 years 9 months ago
Composite Models of Objects and Scenes for Category Recognition
This paper presents a method of learning and recognizing generic object categories using part-based spatial models. The models are multiscale, with a scene component that specifie...
David J. Crandall, Daniel P. Huttenlocher
CVPR
2010
IEEE
13 years 7 months ago
Scene understanding by statistical modeling of motion patterns
We present a novel method for the discovery and statistical representation of motion patterns in a scene observed by a static camera. Related methods involving learning of pattern...
Imran Saleemi, Lance Hartung, Mubarak Shah
CVPR
2007
IEEE
14 years 1 months ago
Unsupervised Learning of Hierarchical Semantics of Objects (hSOs)
A successful representation of objects in the literature is as a collection of patches, or parts, with a certain appearance and position. The relative locations of the different p...
Devi Parikh, Tsuhan Chen
TSP
2010
13 years 2 months ago
Gaussian multiresolution models: exploiting sparse Markov and covariance structure
We consider the problem of learning Gaussian multiresolution (MR) models in which data are only available at the finest scale and the coarser, hidden variables serve both to captu...
Myung Jin Choi, Venkat Chandrasekaran, Alan S. Wil...
PAMI
2010
205views more  PAMI 2010»
13 years 6 months ago
Learning a Hierarchical Deformable Template for Rapid Deformable Object Parsing
In this paper, we address the tasks of detecting, segmenting, parsing, and matching deformable objects. We use a novel probabilistic object model that we call a hierarchical defor...
Long Zhu, Yuanhao Chen, Alan L. Yuille