| Author(s): |
Xiaolan Li; Afzal A. Godil; Asim Wagan; |
| Title: |
Spatially Enhanced Bags of Words for 3D Shape Retrieval |
| Published: |
December 03, 2008 |
| Abstract: |
This paper presents a new method for 3D shape retrieval based on the bags-of-words model along with a weak spatial constraint. First, a two-pass sampling procedure is performed to extract the local shape descriptors, based on spin images, which are used to construct a shape dictionary. Second, the model is partitioned into different regions based on the positions of the words. Then each region is denoted as a histogram of words (also known as bag-of-words) as found in it along with its position. After that, the 3D model is represented as the collection of histograms, denoted as bags-of-words, along with their relative positions, which is an extension of an orderless bag-of-words 3D shape repre-sentation. We call it as Spatial Enhanced Bags-of-Words (SEBW). The spatial constraint shows improved performance on 3D shape retrieval tasks. |
| Conference: |
4th International Symposium on Visual Computing |
| Proceedings: |
Proceeding of the 4th International Symposium on Visual Computing |
| Volume: |
5358 |
| Pages: |
pp. 349 - 358 |
| Location: |
Las Vegas, NV |
| Dates: |
December 1-3, 2008 |
| Keywords: |
spin image, bag of words, 3D shape retrieval |
| Research Areas: |
Data and Informatics |
| PDF version: |
 Click here to retrieve PDF version of paper (785KB) |
