Representation and Detection of Shapes in Images
We present a set of techniques that can be used to represent anddetect shapes in images. Our methods revolve around a particularshape representation based on the description of objects usingtriangulated polygons. This representation is similar to the medialaxis transform and has important properti...
| Main Author: | |
|---|---|
| Language: | en_US |
| Published: |
2005
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/1721.1/30400 |
| _version_ | 1811079507060195328 |
|---|---|
| author | Felzenszwalb, Pedro F. |
| author_facet | Felzenszwalb, Pedro F. |
| author_sort | Felzenszwalb, Pedro F. |
| collection | MIT |
| description | We present a set of techniques that can be used to represent anddetect shapes in images. Our methods revolve around a particularshape representation based on the description of objects usingtriangulated polygons. This representation is similar to the medialaxis transform and has important properties from a computationalperspective. The first problem we consider is the detection ofnon-rigid objects in images using deformable models. We present anefficient algorithm to solve this problem in a wide range ofsituations, and show examples in both natural and medical images. Wealso consider the problem of learning an accurate non-rigid shapemodel for a class of objects from examples. We show how to learn goodmodels while constraining them to the form required by the detectionalgorithm. Finally, we consider the problem of low-level imagesegmentation and grouping. We describe a stochastic grammar thatgenerates arbitrary triangulated polygons while capturing Gestaltprinciples of shape regularity. This grammar is used as a prior modelover random shapes in a low level algorithm that detects objects inimages. |
| first_indexed | 2024-09-23T11:16:09Z |
| id | mit-1721.1/30400 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T11:16:09Z |
| publishDate | 2005 |
| record_format | dspace |
| spelling | mit-1721.1/304002019-04-12T08:26:01Z Representation and Detection of Shapes in Images Felzenszwalb, Pedro F. AI We present a set of techniques that can be used to represent anddetect shapes in images. Our methods revolve around a particularshape representation based on the description of objects usingtriangulated polygons. This representation is similar to the medialaxis transform and has important properties from a computationalperspective. The first problem we consider is the detection ofnon-rigid objects in images using deformable models. We present anefficient algorithm to solve this problem in a wide range ofsituations, and show examples in both natural and medical images. Wealso consider the problem of learning an accurate non-rigid shapemodel for a class of objects from examples. We show how to learn goodmodels while constraining them to the form required by the detectionalgorithm. Finally, we consider the problem of low-level imagesegmentation and grouping. We describe a stochastic grammar thatgenerates arbitrary triangulated polygons while capturing Gestaltprinciples of shape regularity. This grammar is used as a prior modelover random shapes in a low level algorithm that detects objects inimages. 2005-12-19T22:44:55Z 2005-12-19T22:44:55Z 2003-08-08 MIT-CSAIL-TR-2003-008 AITR-2003-016 http://hdl.handle.net/1721.1/30400 en_US Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory 80 p. 38103057 bytes 1889641 bytes application/postscript application/pdf application/postscript application/pdf |
| spellingShingle | AI Felzenszwalb, Pedro F. Representation and Detection of Shapes in Images |
| title | Representation and Detection of Shapes in Images |
| title_full | Representation and Detection of Shapes in Images |
| title_fullStr | Representation and Detection of Shapes in Images |
| title_full_unstemmed | Representation and Detection of Shapes in Images |
| title_short | Representation and Detection of Shapes in Images |
| title_sort | representation and detection of shapes in images |
| topic | AI |
| url | http://hdl.handle.net/1721.1/30400 |
| work_keys_str_mv | AT felzenszwalbpedrof representationanddetectionofshapesinimages |