Re-Ranking and rank aggregation approaches for image retrieval tasks
| Grant number: | 14/04220-8 |
| Support type: | Scholarships in Brazil - Scientific Initiation |
| Effective date (Start): | May 01, 2014 |
| Effective date (End): | December 31, 2016 |
| Field of knowledge: | Physical Sciences and Mathematics - Computer Science - Computer Systems |
| Principal Investigator: | Daniel Carlos Guimarães Pedronette |
| Grantee: | Lucas Pascotti Valem |
| Home Institution: | Instituto de Geociências e Ciências Exatas (IGCE). Universidade Estadual Paulista (UNESP). Campus de Rio Claro. Rio Claro , SP, Brazil |
| Associated research grant: | 13/08645-0 - Re-Ranking and rank aggregation approaches for image retrieval tasks, AP.JP |
Abstract Content-Based Image Retrieval (CBIR) systems aims at retrieving the most similar images in a collection by taking into account image visual properties. Users are interested in the images placed at the first positions of the returned ranked lists, which usually are the most relevant ones. Therefore, accurately ranking collection images is of great relevance. However, in general, CBIR approaches perform only pairwise image analysis, that is, they compute similarity (or distance) measures considering only pairs of images, ignoring the rich information encoded in the relationships among images. Aiming at improving the effectiveness of CBIR systems, re-ranking and rank aggregation algorithms have been proposed. The main goal of this project consists in the parallel implementation of a re-ranking method and profiling actions on heterogeneous computing environments, involving CPUs and GPUs. | |