Learning a Hierarchical Deformable Template for Rapid Deformable Object Parsing

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 deformable template (HDT). The HDT represents the object by state variables defined over a hierarchy (with typically five leve...

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Bibliographic Details
Main Authors: Long, Zhu, Chen, Yuanhao, Yuille, Alan
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Format: Article
Language:en_US
Published: Institute of Electrical and Electronics Engineers 2010
Subjects:
Hierarchy
Object parsing
Segmentation
Shape matching
Shape representation
Structured learning
Online Access:http://hdl.handle.net/1721.1/59532

Internet

http://hdl.handle.net/1721.1/59532

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