@inproceedings{8499404d0cd046f3957680703741e9ce,
title = "Towards motion recognition on smartphone",
abstract = "With the advent of digital convergence trends, the current smartphone equipped with more powerful hardware and complex software to satisfy the increased user requirements. Additionally, similar to video game console, the pioneers of smartphone manufacturers consider adopting the motion recognition to extend their functionality. In this paper, we modify a commodity smartphone system to recognize the motion of users using an on-board camera and the OpenCV library. Additionally, we also implement a performance monitoring system which consists of a kernel monitoring module and a user-level logger. Based on the system, we analyze the performance impact and bottleneck of motion recognition with representative smartphone workloads, and propose the points for improvement in term of system architecture.",
keywords = "Motion recognition, OpenCV, Performance, Smartphone",
author = "Kwak, \{Young Tae\} and Heeseung Jo",
year = "2013",
doi = "10.4028/www.scientific.net/AMM.284-287.2561",
language = "English",
isbn = "9783037856123",
series = "Applied Mechanics and Materials",
pages = "2561--2564",
booktitle = "Innovation for Applied Science and Technology",
note = "2nd International Conference on Engineering and Technology Innovation 2012, ICETI 2012 ; Conference date: 02-11-2012 Through 06-11-2012",
}