Low Vision Assistance Using Face Detection and Tracking on Android Smartphones

被引：0

作者：

Savakis, Andreas ^{[1
]}

Stump, Mark ^{[1
]}

Tsagkatakis, Grigorios ^{[1
]}

Melton, Roy ^{[1
]}

Behm, Gary ^{[2
]}

Sterns, Gwen ^{[3
]}

机构：

[1] Rochester Inst Technol, Dept Comp Engn, Rochester, NY 14623 USA

[2] Rochester Inst Technol, Natl Tech Inst Deaf, Rochester, NY 14623 USA

[3] Rochester Gen Hosp, Dept Ophthalmol, Rochester, NY 14621 USA

来源：

2012 IEEE 55TH INTERNATIONAL MIDWEST SYMPOSIUM ON CIRCUITS AND SYSTEMS (MWSCAS) | 2012年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents a low vision assistance system for individuals with blind spots in their visual field. The system identifies prominent faces in the field of view and redisplays them in regions that are visible to the user. As part of the system performance evaluation, we compare various algorithms for face detection and tracking on an Android smartphone, a netbook and a high-performance workstation representative of cloud computing. We examine processing time and energy consumption on all three platforms to determine the tradeoff between processing on a smartphone versus a cloud-desktop after compression and transmission. Our results demonstrate that Viola-Jones face detection along with Lucas-Kanade tracking achieve the best performance and efficiency.

引用

页码：1176 / 1179

页数：4

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