Smartphone-Based Assistance for Blind People to Stand in Lines
Seita Kayukawa, Hironobu Takagi, João Guerreiro, Shigeo Morishima, and Chieko Asakawa
We present a smartphone-based system that assists blind people to stand in lines.
We present a smartphone-based system that assists blind people to stand in lines.
The system uses a built-in RGB camera and infrared camera of an off-the shelf smart-phone to estimate the distance to a person in front of the user.
The system uses a built-in RGB camera and infrared camera of an off-the shelf smart-phone to estimate the distance to a person in front of the user.
Based on the distance information provided by vibration alerts, blind users can stop or start moving forward to right position at the right timing.
Based on the distance information provided by vibration alerts, blind users can stop or start moving forward to right position at the right timing.
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Abstract
We present a system to allow blind people to stand in line in public spaces by using an off-the-shelf smartphone only. The technologies to navigate blind pedestrians in public spaces are rapidly improving, but tasks which require to understand surrounding people's behavior are still difficult to assist. Standing in line at shops, stations, and other crowded places is one of such tasks. Therefore, we developed a system to detect and notify the distance to a person in front continuously by using a smartphone with an RGB camera and an infrared depth sensor. The system alerts three levels of distance via vibration patterns to allow users to start/stop moving forward to the right position at the right timing. To evaluate the effectiveness of the system, we performed a study with six blind people. We observed that the system enables blind participants to stand in line successfully, while also gaining more confidence.
Publication
Seita Kayukawa, Hironobu Takagi, João Guerreiro, Shigeo Morishima, and Chieko Asakawa. 2020. Smartphone-Based Assistance for Blind People to Stand in Lines. Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems (CHI EA 2020).
CHI EA 2020 DOI Paper BibTeX
Authors
Waseda University
IBM Research
University of Lisbon
Waseda University
IBM Research
University of Lisbon
Waseda Research Institute for Science and Engineering
IBM Research
Related Project
Masaki Kuribayashi*, Seita Kayukawa*, Hironobu Takagi, Chieko Asakawa, and Shigeo Morishima
(* - equal contribution)
CHI 2021
Media
Acknowledgements
This work was supported by JST ACCEL (JPMJAC1602) and JST-Mirai Program (JPMJMI19B2). We thank Tatsuya Ishihara, Masayuki Murata, Takashi Itoh, and Masashi Oikawa for their support.