An Initial Study of Automatic Curb Ramp Detection with Crowdsourced Verification Using Google Street View Images

Hara, Kotaro; Sun, Jin; Chazan, Jonah; Jacobs, David W.; Froehlich, Jon E.

doi:10.1609/hcomp.v1i1.13109

Cited by 5 publications

(1 citation statement)

References 4 publications

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“…For example, Yin et al [148] and Chen et al [149] used Google Street View imagery to measure the volume of pedestrian footfall on streets. Hara et al [150] accessed Google Street View to classify the accessibility of public transit for blind users, and curb ramp access for pedestrians with mobility challenges [151]. Rundle et al [152] and Kelly et al [153] used Google Street View composites to audit different urban neighborhoods, and Wang et al [154] employed a similar approach to assess whether streetscapes could be deemed as "healthy" or not.…”

Section: Cameras and Computer Visionmentioning

confidence: 99%

Smart and Sentient Retail High Streets

Torrens

2022

Smart Cities

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Here, we examine the extension of smart retailing from the indoor confines of stores, outward to high streets. We explore how several technologies at the union of retail intelligence and smart city monitoring could coalesce into retail high streets that are both smart and sentient. We examine the new vantages that smart and sentient retail high streets provide on the customer journey, and how they could transform retailers’ sway over customer experience with new reach to the public spaces around shops. In doing so, we pursue a three-way consideration of these issues, examining the technology that underpins smart retailing, new advances in artificial intelligence and machine learning that beget a level of street-side sentience, and opportunities for retailers to map the knowledge that those technologies provide to individual customer journeys in outdoor settings. Our exploration of these issues takes form as a review of the literature and the introduction of our own research to prototype smart and sentient retail systems for high streets. The topic of enhancing retailers’ acuity on high streets has significant currency, as many high street stores have recently been struggling to sustain custom. However, the production and application of smart and sentient technologies at hyper-local resolution of the streetscape conjures some sobering considerations about shoppers’ and pedestrians’ rights to privacy in public.

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Section: Cameras and Computer Visionmentioning

confidence: 99%

Smart and Sentient Retail High Streets

Torrens

2022

Smart Cities

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Real-Time Path Generation and Alignment Control for Autonomous Curb Following

Wang,

Dai,

Wang

2024

2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Scalable methods to collect and visualize sidewalk accessibility data for people with mobility impairments

Hara

2014

Proceedings of the Adjunct Publication of the 27th Annual ACM Symposium on User Interface Software and Technology - UIST'14 Adj

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Poorly maintained sidewalks pose considerable accessibility challenges for people with mobility impairments. Despite comprehensive civil rights legislation of Americans with Disabilities Act, many city streets and sidewalks in the U.S. remain inaccessible.The problem is not just that sidewalk accessibility fundamentally affects where and how people travel in cities, but also that there are few, if any, mechanisms to determine accessible areas of a city a priori.To address this problem, my Ph.D. dissertation introduces and evaluates new scalable methods for collecting data about street-level accessibility using a combination of crowdsourcing, automated methods, and Google Street View (GSV). My dissertation has four research threads. First, we conduct a formative interview study to establish a better understanding of how people with mobility impairments currently assess accessibility in the built environment and the role of emerging location-based technologies therein. The study uncovers the existing methods for assessing accessibility of physical environment and identify useful features of future assistive technologies. Second, we develop and evaluate scalable crowdsourced accessibility data collection methods. We show that paid crowd workers recruited from an online labor marketplace can find and label accessibility attributes in GSV with accuracy of 81%. This accuracy improves to 93% with quality control mechanisms such as majority vote. Third, we design a system that combines crowdsourcing and automated methods to increase data collection efficiency. Our work shows that by combining crowdsourcing and automated methods, we can increase data collection efficiency by 13% without sacrificing accuracy. Fourth, we develop and deploy a web tool that lets volunteers to help us collect the street-level accessibility data from Washington, D.C.As of writing this dissertation, we have collected the accessibility data from 20% of the streets in D.C. We conduct a preliminary evaluation on how the said web tool is used.Finally, we implement proof-of-concept accessibility-aware applications with accessibility data collected with the help of volunteers.My dissertation contributes to the accessibility, computer science, and HCI communities by: (i) extending the knowledge of how people with mobility impairments interact with technology to navigate in cities; (ii) introducing the first work that demonstrates that GSV is a viable source for learning about the accessibility of the physical world; (iii) introducing the first method that combines crowdsourcing and automated methods to remotely collect accessibility information; (iv) deploying interactive web tools that allow volunteers to help populate the largest dataset about street-level accessibility of the world; and (v) demonstrating accessibility-aware applications that empower people with mobility impairments.

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An Initial Study of Automatic Curb Ramp Detection with Crowdsourced Verification Using Google Street View Images

Cited by 5 publications

References 4 publications

Smart and Sentient Retail High Streets

Smart and Sentient Retail High Streets

Real-Time Path Generation and Alignment Control for Autonomous Curb Following

Scalable methods to collect and visualize sidewalk accessibility data for people with mobility impairments

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