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ICPR
2008
IEEE
14 years 2 months ago
Flexible object recognition in cluttered scenes using relative point distribution models
This paper introduces an edge-based object recognition method that is robust with respect to clutter, occlusion and object deformations. The method combines the use of local featu...
Alexandros Bouganis, Murray Shanahan
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
ICIP
2005
IEEE
14 years 9 months ago
Joint feature-spatial-measure space: a new approach to highly efficient probabilistic object tracking
In this paper we present a probabilistic framework for tracking objects based on local dynamic segmentation. We view the segn to be a Markov labeling process and abstract it as a ...
Feng Chen, XiaoTong Yuan, ShuTang Yang
PAMI
2010
181views more  PAMI 2010»
13 years 6 months ago
Using Language to Learn Structured Appearance Models for Image Annotation
Abstract— Given an unstructured collection of captioned images of cluttered scenes featuring a variety of objects, our goal is to simultaneously learn the names and appearances o...
Michael Jamieson, Afsaneh Fazly, Suzanne Stevenson...
CVPR
2010
IEEE
1248views Computer Vision» more  CVPR 2010»
14 years 4 months ago
Food Recognition Using Statistics of Pairwise Local Features
Food recognition is difficult because food items are deformable objects that exhibit significant variations in appearance. We believe the key to recognizing food is to exploit the...
Shulin Yang, Mei Chen, Dean Pomerleau, Rahul Sukth...