Authors:
Alexander Gularte
;
Camila Thomasi
;
Rodrigo de Bem
and
Diana Adamatti
Affiliation:
Universidade Federal do Rio Grande (FURG), Brazil
Keyword(s):
Performance Evaluation, Local Features Extraction, Mobile Imaging.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Computer Vision, Visualization and Computer Graphics
;
Features Extraction
;
Image and Video Analysis
;
Mobile Imaging
Abstract:
The great number of researches about local features extraction algorithms in the last years, allied to the
popularization of mobile devices, makes desirable efficient and accurate algorithms suitable to run on such
devices. Despite this, there are few approaches adequate to run efficiently on the complexity-, cost- and
power-constrained mobile environments. The main objective of this work is to evaluate the performance of
the recently proposed BRISK algorithm on mobile devices. In this way, a mobile implementation, named
M-BRISK, is proposed. Some implementation strategies are considered and successful applied to execute the
algorithm in a real-world mobile device. As evaluation criterion repeatability, recall, precision and running
time metrics are used, as well as the comparison with the classical well established algorithm SURF and also
with the more recently proposed ORB. The results confirm that proposed mobile implementation of BRISK
(M-BRISK) performs well and it is adequate t
o mobile devices.
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