Representation and Detection of Shapes in Images

Item

Title: en_US Representation and Detection of Shapes in Images
Creator: en_US Felzenszwalb, Pedro F.
Date: 2004-10-20T20:32:11Z
Date Available: 2004-10-20T20:32:11Z
Date Issued: en_US 2003-08-08
Identifier: en_US AITR-2003-016
uri: http://hdl.handle.net/1721.1/7111
Abstract: en_US We present a set of techniques that can be used to represent and detect shapes in images. Our methods revolve around a particular shape representation based on the description of objects using triangulated polygons. This representation is similar to the medial axis transform and has important properties from a computational perspective. The first problem we consider is the detection of non-rigid objects in images using deformable models. We present an efficient algorithm to solve this problem in a wide range of situations, and show examples in both natural and medical images. We also consider the problem of learning an accurate non-rigid shape model for a class of objects from examples. We show how to learn good models while constraining them to the form required by the detection algorithm. Finally, we consider the problem of low-level image segmentation and grouping. We describe a stochastic grammar that generates arbitrary triangulated polygons while capturing Gestalt principles of shape regularity. This grammar is used as a prior model over random shapes in a low level algorithm that detects objects in images.
Extent: en_US 80 p.; 6877524 bytes; 3132998 bytes
Format: application/postscript; application/pdf
Language: en_US
Relation: en_US AITR-2003-016
Subject: en_US AI

Item sets: AI Technical Reports (1964 - 2004)