A Head-Mounted Assistive Device for Visually Impaired People with Warning System from Object Detection and Depth Estimation

辅助装置 计算机科学 计算机视觉 人工智能 触觉技术 方向(向量空间) 主管(地质) 视力受损 信号(编程语言) 人机交互 物理医学与康复 数学 医学 几何学 地貌学 程序设计语言 地质学
作者
Boonthicha Sae-jia,Rodolfo Lian Paderon,Thatchai Srimuninnimit
出处
期刊:Journal of physics [IOP Publishing]
卷期号:2550 (1): 012034-012034
标识
DOI:10.1088/1742-6596/2550/1/012034
摘要

Abstract People with visual impairment use white cane as their traditional method for perceiving the surroundings. However, the utilization of a cane is limited by its length and orientation. In Thailand, the obstacles on paveway in daily life are not located only on the floor but also above knee level which sometimes could be harmful to pedestrians, especially blind people. A head-mounted assistive device is developed to be an enhancement used with a cane for the visually impaired to comprehend their environment both lower and higher the knee level. The assistive device is designed to be compact and light-weight. It could also send the tactile feedback as a warning from vibration motors mounted on the device. To generate a warning signal, YOLOv4 is used to detect the location of obstacles and depth map from the stereo camera is used to estimate the distance mapping into 4 defined ranges: dangerous, very close, close and fine. The results indicate that the head-mounted assistive device has the ability to perceive obstacles locating farther than 0.9 m. The prediction returned 9.23%, 14.63% and 7.86% error when estimating the depth of obstacles at 1.3 m., 2.8 m. and 4.2 m. respectively. The average execution time for the device to return the command controlling vibration motors is 0.13 second and the maximum estimated time for the motor to send the haptic feedback is 1.05 second.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
小黄应助学术蠕虫采纳,获得10
1秒前
1秒前
Orange应助自觉的小蝴蝶采纳,获得10
2秒前
2秒前
哲999发布了新的文献求助10
2秒前
xiaohu完成签到,获得积分10
3秒前
文艺的毛巾完成签到,获得积分20
3秒前
3秒前
勤快浣熊完成签到 ,获得积分10
3秒前
听风完成签到 ,获得积分10
3秒前
糖果苏扬完成签到 ,获得积分10
4秒前
jasmineee完成签到,获得积分10
4秒前
lurenjia009发布了新的文献求助10
4秒前
Orange应助小橙子采纳,获得10
4秒前
iiing完成签到 ,获得积分10
5秒前
想跟这个世界讲个道理完成签到,获得积分10
5秒前
5秒前
5秒前
Eva发布了新的文献求助10
6秒前
张有志应助本杰明采纳,获得30
6秒前
Dandelion完成签到,获得积分10
6秒前
完美世界应助葛辉辉采纳,获得10
7秒前
龙泉完成签到 ,获得积分10
7秒前
Khr1stINK发布了新的文献求助20
7秒前
美女发布了新的文献求助10
7秒前
汉堡包应助烫嘴普通话采纳,获得10
7秒前
长颈鹿完成签到,获得积分10
9秒前
Koi完成签到,获得积分10
9秒前
打卤完成签到,获得积分10
9秒前
CodeCraft应助Intro采纳,获得10
10秒前
SciGPT应助cat采纳,获得10
10秒前
Minkslion发布了新的文献求助10
10秒前
11秒前
酷波er应助细腻的麦片采纳,获得10
12秒前
lurenjia009完成签到,获得积分10
13秒前
13秒前
科研通AI5应助huangyi采纳,获得10
14秒前
yxy完成签到,获得积分10
14秒前
Orange应助yam001采纳,获得30
14秒前
14秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527723
求助须知:如何正确求助?哪些是违规求助? 3107826
关于积分的说明 9286663
捐赠科研通 2805577
什么是DOI,文献DOI怎么找? 1539998
邀请新用户注册赠送积分活动 716878
科研通“疑难数据库(出版商)”最低求助积分说明 709762