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CVPR
2006
IEEE

The Layout Consistent Random Field for Recognizing and Segmenting Partially Occluded Objects

15 years 26 days ago
The Layout Consistent Random Field for Recognizing and Segmenting Partially Occluded Objects
This paper addresses the problem of detecting and segmenting partially occluded objects of a known category. We first define a part labelling which densely covers the object. Our Layout Consistent Random Field (LayoutCRF) model then imposes asymmetric local spatial constraints on these labels to ensure the consistent layout of parts whilst allowing for object deformation. Arbitrary occlusions of the object are handled by avoiding the assumption that the whole object is visible. The resulting system is both efficient to train and to apply to novel images, due to a novel annealed layout-consistent expansion move algorithm paired with a randomised decision tree classifier. We apply our technique to images of cars and faces and demonstrate state-of-the-art detection and segmentation performance even in the presence of partial occlusion.
John M. Winn, Jamie Shotton
Added 12 Oct 2009
Updated 12 Oct 2009
Type Conference
Year 2006
Where CVPR
Authors John M. Winn, Jamie Shotton
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