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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Fractal dimension of bag-of-visual words

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Author(s):
Ribas, Lucas Correia [1] ; Goncalves, Diogo Nunes [2] ; Silva, Jonathan de Andrade [2] ; de Castro, Jr., Amaury Antonio [2] ; Bruno, Odemir Martinez [3] ; Goncalves, Wesley Nunes [2]
Total Authors: 6
Affiliation:
[1] Univ Sao Paulo, Inst Math & Comp Sci, Ave Trabalhador Sao Carlense 400, BR-13566590 Sao Carlos, SP - Brazil
[2] Univ Fed Mato Grosso do Sul, Rua Itibire Vieira S-N, BR-79907414 Ponta Pora, MS - Brazil
[3] Univ Sao Paulo, Sao Carlos Inst Phys, Ave Trabalhador Sao Carlense 400, POB 369, BR-13560970 Sao Carlos, SP - Brazil
Total Affiliations: 3
Document type: Journal article
Source: PATTERN ANALYSIS AND APPLICATIONS; v. 22, n. 1, p. 89-98, FEB 2019.
Web of Science Citations: 1
Abstract

Scene recognition is an important and challenging problem in computer vision. One of the most used scene recognition methods is the bag-of-visual words. Despite the interesting results, this approach does not capture the detail richness of spatial information of the visual words on the image. In this paper, we propose a new method to describe the visual words using the fractal dimension. Our method estimates the fractal dimension of each visual word on image through box-counting method. The fractal dimension is capable of providing complex and spatial information of the visual words in a simple and efficient way. We validate our method on three well-known scene and object datasets, and the experimental results reveal that our method leads to highly discriminative features of the visual words. In addition, the proposed method has achieved competitive results compared to popular methods in scene classification. (AU)

FAPESP's process: 16/23763-8 - Modeling and analysis of complex networks for computer vision
Grantee:Lucas Correia Ribas
Support type: Scholarships in Brazil - Doctorate
FAPESP's process: 16/18809-9 - Deep learning and complex networks applied to computer vision
Grantee:Odemir Martinez Bruno
Support type: Research Grants - Research Partnership for Technological Innovation - PITE
FAPESP's process: 14/08026-1 - Artificial vision and pattern recognition applied to vegetal plasticity
Grantee:Odemir Martinez Bruno
Support type: Regular Research Grants