Conference proceeding
3D Building Synthesis Based on Images and Affine Invariant Salient Features
PROCEEDINGS OF THE 2ND MEDITERRANEAN CONFERENCE ON PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE (MEDPRAI-2018), v 2018-
01 Jan 2018
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
In this paper', we introduce a method to synthesize and recognize buildings using a set of at least two 2D images taken from different views. Based on a coarse set of affirm invariant salient feature points (corner points) on the images, a 3D high resolution building model is obtained in accordance with the observed images. Corresponding salient points are found using the ratio of triangle areas formed from a set of tour consecutive ordered salient corresponding points that form two triangles. The order is obtained by finding the vertices of the convex hull of the salient points. The salient points are tessellated to form a high resolution triangular mesh with the appearance of a triangular patch in the image imported onto the personalized 31) model. With multiple images, all coordinates and appearance are reconstructed in accordance with the observed images. The 31) model reconstruction method allows for a 31) classification of a test building to one of many possible buildings stored in the database. The classification is based on a geometric 3D point cloud error. For buildings with very close 3D cloud errors, a further classification is achieved based on the mean squared error (MSE) on the appearance of corresponding points on the test and base models. Our method can also he used in localization when preloaded location information of each model in the database is stored, hence helping an observer navigate without a GPS system.
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Details
- Title
- 3D Building Synthesis Based on Images and Affine Invariant Salient Features
- Creators
- Fernand S. Cohen - Drexel UniversityChenxi Li - Drexel UniversityAssoc Comp Machinery
- Publication Details
- PROCEEDINGS OF THE 2ND MEDITERRANEAN CONFERENCE ON PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE (MEDPRAI-2018), v 2018-
- Conference
- 2ND MEDITERRANEAN CONFERENCE ON PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE (MEDPRAI-2018), 2nd
- Publisher
- Assoc Computing Machinery
- Number of pages
- 8
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:000460471100008
- Scopus ID
- 2-s2.0-85047118647
- Other Identifier
- 991019169649704721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Imaging Science & Photographic Technology