| Full text | |
| Author(s): |
Guimaraes Pedronette, Daniel Carlos
[1]
;
Valem, Lucas Pascotti
[1]
;
Almeida, Jurandy
[2]
;
Tones, Ricardo da S.
[3]
Total Authors: 4
|
| Affiliation: | [1] State Univ Sao Paulo, Dept Stat Appl Maths & Comp, BR-13506900 Rio Claro - Brazil
[2] Univ Fed Sao Paulo, Inst Sci & Technol, BR-12231280 Sao Jose Dos Campos - Brazil
[3] Univ Estadual Campinas, Inst Comp, RECOD Lab, BR-13083852 Campinas, SP - Brazil
Total Affiliations: 3
|
| Document type: | Journal article |
| Source: | IEEE Transactions on Image Processing; v. 28, n. 12, p. 5824-5838, DEC 2019. |
| Web of Science Citations: | 0 |
| Abstract | |
Accurately ranking images and multimedia objects are of paramount relevance in many retrieval and learning tasks. Manifold learning methods have been investigated for ranking mainly due to their capacity of taking into account the intrinsic global manifold structure. In this paper, a novel manifold ranking algorithm is proposed based on the hypergraphs for unsupervised multimedia retrieval tasks. Different from traditional graph-based approaches, which represent only pairwise relationships, hypergraphs are capable of modeling similarity relationships among a set of objects. The proposed approach uses the hyperedges for constructing a contextual representation of data samples and exploits the encoded information for deriving a more effective similarity function. An extensive experimental evaluation was conducted on nine public datasets including diverse retrieval scenarios and multimedia content. Experimental results demonstrate that high effectiveness gains can be obtained in comparison with the state-of-the-art methods. (AU) | |
| FAPESP's process: | 14/50715-9 - Characterizing and predicting biomass production in sugarcane and eucalyptus plantations in Brazil |
| Grantee: | Rubens Augusto Camargo Lamparelli |
| Support Opportunities: | Research Grants - Research Partnership for Technological Innovation - PITE |
| FAPESP's process: | 16/50250-1 - The secret of playing football: Brazil versus the Netherlands |
| Grantee: | Sergio Augusto Cunha |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 17/25908-6 - Weakly supervised learning for compressed video analysis on retrieval and classification tasks for visual alert |
| Grantee: | João Paulo Papa |
| Support Opportunities: | Research Grants - Research Partnership for Technological Innovation - PITE |
| FAPESP's process: | 17/20945-0 - Multi-user equipment approved in great 16/50250-1: local positioning system |
| Grantee: | Sergio Augusto Cunha |
| Support Opportunities: | Multi-user Equipment Program |
| FAPESP's process: | 14/12236-1 - AnImaLS: Annotation of Images in Large Scale: what can machines and specialists learn from interaction? |
| Grantee: | Alexandre Xavier Falcão |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 16/06441-7 - Semantic information retrieval in large video databases |
| Grantee: | Jurandy Gomes de Almeida Junior |
| Support Opportunities: | Regular Research Grants |
| FAPESP's process: | 18/15597-6 - Aplication and investigation of unsupervised learning methods in retrieval and classification tasks |
| Grantee: | Daniel Carlos Guimarães Pedronette |
| Support Opportunities: | Research Grants - Young Investigators Grants - Phase 2 |
| FAPESP's process: | 13/50155-0 - Combining new technologies to monitor phenology from leaves to ecosystems |
| Grantee: | Leonor Patricia Cerdeira Morellato |
| Support Opportunities: | Research Program on Global Climate Change - University-Industry Cooperative Research (PITE) |
| FAPESP's process: | 17/02091-4 - Selection and combination of unsupervised learning Methdos for content-based image retrieval |
| Grantee: | Lucas Pascotti Valem |
| Support Opportunities: | Scholarships in Brazil - Master |
| FAPESP's process: | 15/24494-8 - Communications and processing of big data in cloud and fog computing |
| Grantee: | Nelson Luis Saldanha da Fonseca |
| Support Opportunities: | Research Projects - Thematic Grants |