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» Learning Hierarchical Models of Scenes, Objects, and Parts
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ICIP
2007
IEEE
15 years 11 months ago
Unsupervised Modeling of Object Tracks for Fast Anomaly Detection
A key goal of far-field activity analysis is to learn the usual pattern of activity in a scene and to detect statistically anomalous behavior. We propose a method for unsupervised...
Tomas Izo, W. Eric L. Grimson
PAMI
2010
205views more  PAMI 2010»
14 years 8 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
ICVGIP
2004
14 years 11 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...
CCIA
2005
Springer
15 years 3 months ago
Classifying Natural Objects on Outdoor Scenes
We propose an hybrid and probabilistic classification of image regions belonging to scenes primarily containing natural objects, e.g. sky, trees, etc. as a first step in solving ...
Anna Bosch, Xavier Muñoz, Joan Martí...
JCISE
2002
128views more  JCISE 2002»
14 years 9 months ago
A Collaborative Framework for Integrated Part and Assembly Modeling
An ideal product modeling system should support both part modeling and assembly modeling, instead of just either of them as is the case in most current CAD systems. A good basis f...
Rafael Bidarra, Niels Kranendonk, Alex Noort, Will...