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Towards Street Camera-based Outdoor Navigation for Blind Pedestrians

Published: 22 October 2023 Publication History

Abstract

Blind and low-vision (BLV) people use GPS-based systems for outdoor navigation assistance, which provide instructions to get from one place to another. However, such systems do not provide users with real-time, precise information about their location and surroundings which is crucial for safe navigation. In this work, we investigate whether street cameras can be used to address aspects of navigation that BLV people still find challenging with existing GPS-based assistive technologies. We conducted formative interviews with six BLV participants to identify specific challenges they face in outdoor navigation. We discovered three main challenges: anticipating environment layouts, avoiding obstacles while following directions, and crossing noisy street intersections. To address these challenges, we are currently developing a street camera-based navigation system that provides real-time auditory feedback to help BLV users avoid obstacles, know exactly when to cross the street, and understand the overall layout of the environment. We close by discussing our evaluation plan.

References

[1]
Dragan Ahmetovic, Cole Gleason, Chengxiong Ruan, Kris Kitani, Hironobu Takagi, and Chieko Asakawa. 2016. NavCog: A navigational cognitive assistant for the blind. In Proceedings of the 18th International Conference on Human-Computer Interaction with Mobile Devices and Services(MobileHCI ’16). Association for Computing Machinery, New York, NY, USA, 90–99. https://doi.org/10.1145/2935334.2935361
[2]
Dragan Ahmetovic, Roberto Manduchi, James M. Coughlan, and Sergio Mascetti. 2017. Mind Your Crossings: Mining GIS Imagery for Crosswalk Localization. ACM Transactions on Accessible Computing 9, 4 (Dec. 2017), 1–25. https://doi.org/10.1145/3046790
[3]
Amnesty International. 2021. Surveillance City: NYPD can use more than 15,000 cameras to track people using facial recognition in Manhattan, Bronx and Brooklyn. https://www.amnesty.org/en/latest/news/2021/06/scale-new-york-police-facial-recognition-revealed/
[4]
Wen-Chung Chang, Chia-Hung Wu, Wen-Ting Luo, and Huan-Chen Ling. 2013. Mobile robot navigation and control with monocular surveillance cameras. In 2013 CACS International Automatic Control Conference (CACS). 192–197. https://doi.org/10.1109/CACS.2013.6734131
[5]
Coco Feng. 2019. China the most surveilled nation? The US has the largest number of CCTV cameras per capita. https://www.scmp.com/tech/gear/article/3040974/china-most-surveilled-nation-us-has-largest-number-cctv-cameras-capita
[6]
COSMOS Project. 2023. Hardware: Cameras. https://wiki.cosmos-lab.org/wiki/Hardware/Cameras
[7]
Ping-Jung Duh, Yu-Cheng Sung, Liang-Yu Fan Chiang, Yung-Ju Chang, and Kuan-Wen Chen. 2020. V-eye: A vision-based navigation system for the visually impaired. IEEE Transactions on Multimedia 23 (2020), 1567–1580.
[8]
Alexander Fiannaca, Ilias Apostolopoulous, and Eelke Folmer. 2014. Headlock: a wearable navigation aid that helps blind cane users traverse large open spaces. In Proceedings of the 16th international ACM SIGACCESS conference on Computers & accessibility(ASSETS ’14). Association for Computing Machinery, New York, NY, USA, 323–324. https://doi.org/10.1145/2661334.2661344
[9]
John C. Flanagan. 1954. The critical incident technique. Psychological Bulletin 51, 4 (1954), 327–358.
[10]
Frank Hersey. 2017. China to have 626 million surveillance cameras within 3 years. https://technode.com/2017/11/22/china-to-have-626-million-surveillance-cameras-within-3-years/
[11]
Leo A. Goodman. 1961. Snowball Sampling. The Annals of Mathematical Statistics 32, 1 (1961), 148–170. https://www.jstor.org/stable/2237615 Publisher: Institute of Mathematical Statistics.
[12]
João Guerreiro, Daisuke Sato, Saki Asakawa, Huixu Dong, Kris M. Kitani, and Chieko Asakawa. 2019. CaBot: Designing and Evaluating an Autonomous Navigation Robot for Blind People. In The 21st International ACM SIGACCESS Conference on Computers and Accessibility(ASSETS ’19). Association for Computing Machinery, New York, NY, USA, 68–82. https://doi.org/10.1145/3308561.3353771
[13]
Richard Guy and Khai Truong. 2012. CrossingGuard: exploring information content in navigation aids for visually impaired pedestrians. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, Austin Texas USA, 405–414. https://doi.org/10.1145/2207676.2207733
[14]
David L Harkey, Daniel L Carter, Janet M Barlow, and Billie Louise Bentzen. 2007. Accessible pedestrian signals: A guide to best practices. National Cooperative Highway Research Program, Contractor’s Guide for NCHRP Project (2007).
[15]
Microsoft Inc.2018. Microsoft Soundscape - Microsoft Research.https://www.microsoft.com/en- us/research/product/soundscape/. (2018).
[16]
Gaurav Jain, Yuanyang Teng, Dong Heon Cho, Yunhao Xing, Maryam Aziz, and Brian A. Smith. 2023. "I Want to Figure Things Out": Supporting Exploration in Navigation for People with Visual Impairments. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 63:1–63:28. https://doi.org/10.1145/3579496
[17]
Hernisa Kacorri, Sergio Mascetti, Andrea Gerino, Dragan Ahmetovic, Valeria Alampi, Hironobu Takagi, and Chieko Asakawa. 2018. Insights on Assistive Orientation and Mobility of People with Visual Impairment Based on Large-Scale Longitudinal Data. ACM Transactions on Accessible Computing 11, 1 (April 2018), 1–28. https://doi.org/10.1145/3178853
[18]
Robert K Katzschmann, Brandon Araki, and Daniela Rus. 2018. Safe local navigation for visually impaired users with a time-of-flight and haptic feedback device. IEEE Transactions on Neural Systems and Rehabilitation Engineering 26, 3 (2018).
[19]
Laura Griffin. 2020. Surveillance Cameras Are Everywhere. And They’re Only Going To Get More Ubiquitous. https://crimereads.com/surveillance-cameras-are-everywhere-and-theyre-only-going-to-get-more-ubiquitous/
[20]
Jaewook Lee, Jaylin Herskovitz, Yi-Hao Peng, and Anhong Guo. 2022. ImageExplorer: Multi-Layered Touch Exploration to Encourage Skepticism Towards Imperfect AI-Generated Image Captions. In CHI Conference on Human Factors in Computing Systems. ACM, New Orleans LA USA, 1–15. https://doi.org/10.1145/3491102.3501966
[21]
Xiang Li, Hanzhang Cui, John-Ross Rizzo, Edward Wong, and Yi Fang. 2020. Cross-Safe: A Computer Vision-Based Approach to Make All Intersection-Related Pedestrian Signals Accessible for the Visually Impaired. In Advances in Computer Vision, Kohei Arai and Supriya Kapoor (Eds.). Vol. 944. Springer International Publishing, Cham, 132–146. https://doi.org/10.1007/978-3-030-17798-0_13
[22]
Yimin Lin, Kai Wang, Wanxin Yi, and Shiguo Lian. 2019. Deep Learning Based Wearable Assistive System for Visually Impaired People. In 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW). IEEE, Seoul, Korea (South), 2549–2557. https://doi.org/10.1109/ICCVW.2019.00312
[23]
Liza Lin, Newley Purnell. 2019. A World With a Billion Cameras Watching You Is Just Around the Corner. https://www.wsj.com/articles/a-billion-surveillance-cameras-forecast-to-be-watching-within-two-years-11575565402
[24]
Sergio Mascetti, Dragan Ahmetovic, Andrea Gerino, and Cristian Bernareggi. 2016. ZebraRecognizer: Pedestrian crossing recognition for people with visual impairment or blindness. Pattern Recognition 60 (Dec. 2016), 405–419. https://doi.org/10.1016/j.patcog.2016.05.002
[25]
MIPsoft. 2016. BlindSquare. https://www.blindsquare.com/
[26]
Marko Modsching, Ronny Kramer, and Klaus ten Hagen. 2006. Field trial on GPS Accuracy in a medium size city: The influence of built-up. In 3rd workshop on positioning, navigation and communication, Vol. 2006. 209–218.
[27]
Petr Oščádal, Daniel Huczala, Jan Bém, Václav Krys, and Zdenko Bobovský. 2020. Smart Building Surveillance System as Shared Sensory System for Localization of AGVs. Applied Sciences 10, 23 (Nov. 2020), 8452. https://doi.org/10.3390/app10238452
[28]
Sabrina A. Paneels, Dylan Varenne, Jeffrey R. Blum, and Jeremy R. Cooperstock. 2013. The Walking Straight Mobile Application: Helping the Visually Impaired Avoid Veering. (July 2013).
[29]
Jagannadh Pariti, Vinita Tibdewal, and Tae Oh. 2020. Intelligent Mobility Cane - Lessons Learned from Evaluation of Obstacle Notification System using a Haptic Approach. In Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems. ACM, Honolulu HI USA, 1–8. https://doi.org/10.1145/3334480.3375217
[30]
Roman Pflugfelder and Horst Bischof. 2010. Localization and Trajectory Reconstruction in Surveillance Cameras with Nonoverlapping Views. IEEE transactions on pattern analysis and machine intelligence 32 (April 2010), 709–21. https://doi.org/10.1109/TPAMI.2009.56
[31]
Giorgio Presti, Dragan Ahmetovic, Mattia Ducci, Cristian Bernareggi, Luca Ludovico, Adriano Baratè, Federico Avanzini, and Sergio Mascetti. 2019. WatchOut: Obstacle Sonification for People with Visual Impairment or Blindness. In The 21st International ACM SIGACCESS Conference on Computers and Accessibility. ACM, Pittsburgh PA USA, 402–413. https://doi.org/10.1145/3308561.3353779
[32]
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever. 2021. Learning Transferable Visual Models From Natural Language Supervision. http://arxiv.org/abs/2103.00020 arXiv:2103.00020 [cs].
[33]
Lisa Ran, Sumi Helal, and Steve Moore. 2004. Drishti: an integrated indoor/outdoor blind navigation system and service. In Second IEEE Annual Conference on Pervasive Computing and Communications, 2004. Proceedings of the. IEEE, 23–30.
[34]
Dipankar Raychaudhuri, Ivan Seskar, Gil Zussman, Thanasis Korakis, Dan Kilper, Tingjun Chen, Jakub Kolodziejski, Michael Sherman, Zoran Kostic, Xiaoxiong Gu, 2020. Challenge: COSMOS: A city-scale programmable testbed for experimentation with advanced wireless. In Proc. ACM MobiCom.
[35]
Daisuke Sato, Uran Oh, João Guerreiro, Dragan Ahmetovic, Kakuya Naito, Hironobu Takagi, Kris M. Kitani, and Chieko Asakawa. 2019. NavCog3 in the Wild: Large-scale Blind Indoor Navigation Assistant with Semantic Features. ACM Transactions on Accessible Computing 12, 3 (Sept. 2019), 1–30. https://doi.org/10.1145/3340319
[36]
Jae Shim and Young Cho. 2016. A Mobile Robot Localization via Indoor Fixed Remote Surveillance Cameras. Sensors 16, 2 (Feb. 2016), 195. https://doi.org/10.3390/s16020195
[37]
Hojun Son, Divya Krishnagiri, V. Swetha Jeganathan, and James Weiland. 2020. Crosswalk Guidance System for the Blind. In 2020 42nd Annual International Conference of the IEEE Engineering in Medicine Biology Society (EMBC). 3327–3330. https://doi.org/10.1109/EMBC44109.2020.9176623 ISSN: 2694-0604.
[38]
Wim Taymans, Steve Baker, Andy Wingo, Rondald S Bultje, and Stefan Kost. 2013. Gstreamer application development manual (1.2. 3). Publicado en la Web 72 (2013).
[39]
Juan Terven and Diana Cordova-Esparza. 2023. A comprehensive review of YOLO: From YOLOv1 to YOLOv8 and beyond. arXiv preprint arXiv:2304.00501 (2023).
[40]
Charles Vicek, Patricia McLain, and Michael Murphy. 1993. GPS/dead reckoning for vehicle tracking in the" urban canyon" environment. In Proceedings of VNIS’93-Vehicle Navigation and Information Systems Conference. IEEE, 461–34.
[41]
Hsueh-Cheng Wang, Robert K. Katzschmann, Santani Teng, Brandon Araki, Laura Giarre, and Daniela Rus. 2017. Enabling independent navigation for visually impaired people through a wearable vision-based feedback system. In 2017 IEEE International Conference on Robotics and Automation (ICRA). IEEE, Singapore, Singapore, 6533–6540. https://doi.org/10.1109/ICRA.2017.7989772
[42]
Shiyun Yang, Emily Bailey, Zhengye Yang, Jonatan Ostrometzky, Gil Zussman, Ivan Seskar, and Zoran Kostic. 2020. COSMOS smart intersection: Edge compute and communications for bird’s eye object tracking. In Proc. SmartEdge.
[43]
Chris Yoon, Ryan Louie, Jeremy Ryan, MinhKhang Vu, Hyegi Bang, William Derksen, and Paul Ruvolo. 2019. Leveraging Augmented Reality to Create Apps for People with Visual Disabilities: A Case Study in Indoor Navigation. In The 21st International ACM SIGACCESS Conference on Computers and Accessibility. ACM, Pittsburgh PA USA, 210–221. https://doi.org/10.1145/3308561.3353788

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  • (2024)StreetNav: Leveraging Street Cameras to Support Precise Outdoor Navigation for Blind PedestriansProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology10.1145/3654777.3676333(1-21)Online publication date: 13-Oct-2024

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    cover image ACM Conferences
    ASSETS '23: Proceedings of the 25th International ACM SIGACCESS Conference on Computers and Accessibility
    October 2023
    1163 pages
    ISBN:9798400702204
    DOI:10.1145/3597638
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    Published: 22 October 2023

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    Author Tags

    1. Visual impairments
    2. computer vision
    3. outdoor navigation
    4. street camera
    5. testbed evaluation

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    • (2024)StreetNav: Leveraging Street Cameras to Support Precise Outdoor Navigation for Blind PedestriansProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology10.1145/3654777.3676333(1-21)Online publication date: 13-Oct-2024

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