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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.)

Application-Oriented Retinal Image Models for Computer Vision

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Silva, Ewerton [1] ; Torres, Ricardo da S. [2] ; Pinto, Allan [1] ; Li, Lin Tzy [1] ; Vianna, Jose Eduardo S. [1] ; Azevedo, Rodolfo [1] ; Goldenstein, Siome [1]
Total Authors: 7
[1] Univ Estadual Campinas, Inst Comp, BR-13083852 Campinas - Brazil
[2] Norwegian Univ Sci & Technol, Dept ICT & Nat Sci, Alesund 2, N-6009 Larsgardsvegen - Norway
Total Affiliations: 2
Document type: Journal article
Source: SENSORS; v. 20, n. 13 JUL 2020.
Web of Science Citations: 0

Energy and storage restrictions are relevant variables that software applications should be concerned about when running in low-power environments. In particular, computer vision (CV) applications exemplify well that concern, since conventional uniform image sensors typically capture large amounts of data to be further handled by the appropriate CV algorithms. Moreover, much of the acquired data are often redundant and outside of the application's interest, which leads to unnecessary processing and energy spending. In the literature, techniques for sensing and re-sampling images in non-uniform fashions have emerged to cope with these problems. In this study, we propose Application-Oriented Retinal Image Models that define a space-variant configuration of uniform images and contemplate requirements of energy consumption and storage footprints for CV applications. We hypothesize that our models might decrease energy consumption in CV tasks. Moreover, we show how to create the models and validate their use in a face detection/recognition application, evidencing the compromise between storage, energy, and accuracy. (AU)

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 type: Research Projects - Thematic Grants
FAPESP's process: 13/50155-0 - Combining new technologies to monitor phenology from leaves to ecosystems
Grantee:Leonor Patricia Cerdeira Morellato
Support type: Research Program on Global Climate Change - University-Industry Cooperative Research (PITE)
FAPESP's process: 16/50250-1 - The secret of playing football: Brazil versus the Netherlands
Grantee:Sergio Augusto Cunha
Support type: Research Projects - Thematic Grants
FAPESP's process: 14/50715-9 - Characterizing and predicting biomass production in sugarcane and eucalyptus plantations in Brazil
Grantee:Rubens Augusto Camargo Lamparelli
Support type: 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 type: Multi-user Equipment Program