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» Learning Statistical Structure for Object Detection
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CVPR
2007
IEEE
14 years 9 months ago
Learning the Compositional Nature of Visual Objects
The compositional nature of visual objects significantly limits their representation complexity and renders learning of structured object models tractable. Adopting this modeling ...
Björn Ommer, Joachim M. Buhmann
CVPR
2010
IEEE
14 years 3 months ago
Modeling Mutual Context of Object and Human Pose in Human-Object Interaction Activities
Detecting objects in cluttered scenes and estimating articulated human body parts are two challenging problems in computer vision. The difficulty is particularly pronounced in ac...
Bangpeng Yao, Li Fei-Fei
CVPR
2001
IEEE
14 years 9 months ago
Feature Reduction and Hierarchy of Classifiers for Fast Object Detection in Video Images
We present a two-step method to speed-up object detection systems in computer vision that use Support Vector Machines (SVMs) as classifiers. In a first step we perform feature red...
Bernd Heisele, Thomas Serre, Sayan Mukherjee, Toma...
ICPR
2008
IEEE
14 years 8 months ago
Image objects and multi-scale features for annotation detection
This paper investigates several issues in the problem of detecting handwritten markings, or annotations, on printed documents. One issue is to define the appropriate units over wh...
Eric Saund, Jindong Chen, Yizhou Wang
NIPS
2001
13 years 8 months ago
Probabilistic principles in unsupervised learning of visual structure: human data and a model
To find out how the representations of structured visual objects depend on the co-occurrence statistics of their constituents, we exposed subjects to a set of composite images wit...
Shimon Edelman, Benjamin P. Hiles, Hwajin Yang, Na...