Descending Stairs Detection with Low-Power Sensors

Cloix, Séverine; Bologna, Guido; Weiss, Viviana; Pun, Thierry; Hasler, David

doi:10.1007/978-3-319-16199-0_46

Cited by 5 publications

(5 citation statements)

References 16 publications

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“…However, staircases are also one of the most dangerous obstacles. Descending stairs are the most dangerous hazards for visually impaired especially those who use rollator or wheelchair [4]. Stacey reported a tragedy where a blind, wheelchairbound teenager broke her neck and died after falling down from the stairs [5].…”

Section: A Challenges Faced By the Visually Impairedmentioning

confidence: 99%

A Ground Plane Hazards Detection Tool for the Visually Impaired

Chun¹,

WeiYen²,

Deverell³

et al. 2018

IJMERR

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The World Health Organization (WHO) reported an estimation of 36 million people who are legally blind this number is expected to be triple. One of the most important effects of vision loss is the loss of ability to travel around safely and independently. In general, the major problems encountered involve obstacles in the pathway and ground plane hazards. The ground plane hazards include the staircases, steps, potholes, pits, ramps, and drainage. Over the years, most of the existing smart devices focus more on the obstacle detection in the surroundings rather than the ground plane hazards which can turn out to be dangerous for the visually impaired. Thus, this project specifically focuses on the development of a smart detection tool for alerting the visually impaired on ground plane hazards. This paper discusses the prototype which is able to detect ground plane hazards like staircases, ramps, drainage and potholes. A real time detection test was conducted and the results proved that the prototype performs up to the expectation in real time. 

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Section: A Challenges Faced By the Visually Impairedmentioning

confidence: 99%

A Ground Plane Hazards Detection Tool for the Visually Impaired

Chun¹,

WeiYen²,

Deverell³

et al. 2018

IJMERR

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“…For the following sections, we will focus on classifying problems of dangerous situations versus the others and dangerous situations versus safe. Our previous study assessed that the scenes illuminance affects the quality of the resulting depth maps [4]. While RGBD cameras are unable to work under bright sunlight [24], passive stereo cameras' performance drastically drops under low or bright illumination unless the sensors have a high dynamic range.…”

Section: Resolution Studymentioning

confidence: 99%

“…In our previous work [4], we presented promising preliminary results of the evaluation of our stairs detection approach that employs depth information obtained from a stereo vision algorithm based on SAD (sum of absolute difference) methods that are known to be adapted to realtime. In this article, as an extension of our previous work [4], we focus on three types of experiments.…”

Section: Introductionmentioning

confidence: 99%

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Low-power depth-based descending stair detection for smart assistive devices

Cloix

Bologna

Weiss

et al. 2016

J Image Video Proc.

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Assistive technologies aim at improving personal mobility of individuals with disabilities, increasing their independence and their access to social life. They include mechanical mobility aids that are increasingly employed amongst the older people who rely on them. However, these devices might fail to prevent falls due to the under-estimation of approaching hazards. Stairs and curbs are among these potential dangers present in urban environments and living accommodations, which increase the risk of an accident. We present and evaluate a low-complexity algorithm to detect descending stairs and curbs of any shape, specifically designed for low-power real-time embedded platforms. Based on a passive stereo camera, as opposed to a 3D active sensor, we assessed the detection accuracy, processing time and power consumption. Our goal being to decide on three possible situations (safe, dangerous and potentially unsafe), we achieve to distinguish more than 94 % dangers from safe scenes within a 91 % overall recognition rate at very low resolution. This is accomplished in real-time with robustness to indoor/outdoor lighting conditions. We show that our method can run for a day on a smartphone battery.

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“…In any case, staircases are also one of the most dangerous obstacles to people with visual impairment. Descending staircases are the most dangerous hazards for visually impaired who utilise rollator or wheelchair [5]. In 2016, Stacey reported a tragedy in which a blind, wheelchairbound teenager suffered from a broken neck and passed away after falling from the stairs [6].…”

Section: Introductionmentioning

confidence: 99%

Exploring the outdoor performance of a LiDAR-based ground plane checking system for the visually impaired

Chai¹

2020

EAI Endorsed Trans Perv Health Tech

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INTRODUCTION: Individuals with visual impairments face a variety of challenges in their daily lives, from daily activities to physical world navigation. One of the biggest challenges is the ability to travel around safely and independently. This challenge is complicated and stressed to the visually impaired as the inability to perform obstacles or ground plane checking will result in severe injury or even death. OBJECTIVES: This work aims to prove the outdoor performance of the developed solution in detecting and recognising the frontal ground plane conditions. METHODS: The proposed model uses a LiDAR module as a distance-measuring tool to perform ground plane checking. RESULTS: In the selected outdoor path-based scenarios, the ground plane checking system succeeded in achieving an overall recognition rate of 93.10%, with an overall false positive rate of 2.72% and average false negative rate of 4.25%. CONCLUSION: Overall, the findings showed the ability of the proposed model to provide effective frontal ground plane checking for the visually impaired.

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Descending Stairs Detection with Low-Power Sensors

Cited by 5 publications

References 16 publications

A Ground Plane Hazards Detection Tool for the Visually Impaired

A Ground Plane Hazards Detection Tool for the Visually Impaired

Low-power depth-based descending stair detection for smart assistive devices

Exploring the outdoor performance of a LiDAR-based ground plane checking system for the visually impaired

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