Adaptive frame-rate optimization for energy-efficient object tracking

Yusuke Inoue, Takatsugu Ono, Koji Inoue

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

3 Citations (Scopus)

Abstract

On-line object tracking (OLOT) has been a core technology in computer vision, and its importance has been increasing rapidly. Because this technology is utilized for battery-operated products, energy consumption must be minimized. This paper describes a method of adaptive frame-rate optimization to satisfy that requirement. An energy trade-off occurs between image capturing and object tracking. Therefore, the method optimizes the frame-rate based on always changed object speed for minimizing the total energy while taking into account the trade-off. Simulation results show a maximum energy reduction of 50.0%, and an average reduction of 35.9% without serious tracking accuracy degradation.

Original languageEnglish
Title of host publicationProceedings of the 2016 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2016
EditorsHamid R. Arabnia, Leonidas Deligiannidis, Fernando G. Tinetti, Jane You, George Jandieri, George Jandieri, Iakov Korovin, Gerald Schaefer, Kok Swee Sim, Ashu M. G. Solo
PublisherCSREA Press
Pages158-164
Number of pages7
ISBN (Electronic)1601324421, 9781601324429
Publication statusPublished - Jan 1 2016
Event2016 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2016 - Las Vegas, United States
Duration: Jul 25 2016Jul 28 2016

Publication series

NameProceedings of the 2016 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2016

Conference

Conference2016 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2016
CountryUnited States
CityLas Vegas
Period7/25/167/28/16

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design

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