An implementation of an affine BRISK for mobile heterogeneous parallel processors

Chulhee Lee, Chae Eun Rhee, Hyuk Jae Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

As the computing power of a mobile processor increases, a number of computer vision applications are widely used by a mobile device. Feature extraction is one of the crucial tasks in a computer vision area and it is used for object recognition, panorama image generation and so on. The affine SIFT (ASIFT) feature is robust to scale, rotation and viewpoint changes but its high computational complexity makes it challenging for ASIFT to be used in applications by a mobile device. To reduce the complexity of ASIFT while maintaining affine invariance, this paper proposes an affine BRISK which replaces SIFT by BRISK of which complexity is much less than SIFT. By fully exploiting the parallelism of affine transformation for viewpoint invariance, this paper achieves the speed up by parallel execution of feature extraction and affine transformation running on the mobile CPU and GPU, respectively. The proposed affine BRISK feature is robust to a viewpoint change with a comparable accuracy. The processing time is 290.64ms on a Galaxy LTE-A mobile.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Consumer Electronics, ICCE 2016
EditorsFrancisco J. Bellido, Daniel Diaz-Sanchez, Nicholas C. H. Vun, Carsten Dolar, Wing-Kuen Ling
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages435-436
Number of pages2
ISBN (Electronic)9781467383646
DOIs
Publication statusPublished - 2016 Mar 10
EventIEEE International Conference on Consumer Electronics, ICCE 2016 - Las Vegas, United States
Duration: 2016 Jan 72016 Jan 11

Publication series

Name2016 IEEE International Conference on Consumer Electronics, ICCE 2016

Other

OtherIEEE International Conference on Consumer Electronics, ICCE 2016
CountryUnited States
CityLas Vegas
Period16/1/716/1/11

Bibliographical note

Funding Information:
This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the ITRC(Information Technology Research Center) support program (IITP-2015-H8501-15-1005) supervised by the IITP(Institute for Information and communications Technology Promotion) and by the Industrial Strategic Technology Development Program (10041664, The Development of Fusion Processor based on Multi-Shader GPU) funded by the Ministry Of Trade, Industry and Energy (MOTIE, Korea)

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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