Real-Time Walk Light Detection with a Mobile Phone

Smart traffic lights for people with visual impairments: A literature overview and a proposed implementation

Attempting to establish aids for individuals who are visually impaired has urged many cities to seek solutions for improving their quality of life. Namely, cities have installed sound-emitting devices into traffic lights as well as sidewalks that assist their navigation. Moreover, as cities are always striving to move forward and achieve innovations concerning navigation for disabled individuals, smart traffic lights, capable of synchronizing in real-time according to traffic and individual mobility conditions, are already being installed around the world. This is in line with the adoption of the smart city concept, which involves a set of methodologies and indicators that regulate how cities perform regarding the promotion of citizens’ quality of life. Another important principle is the techno-economic aspect indicating the need for low-cost careful planning to produce cost-efficient solutions, while additional important issues are maintenance, power efficiency, and the means to coordinate numerous devices to facilitate operation in a timely and reliable manner. In this article, we present an overview of the existing solutions for the navigation of people who are blind and visually impaired along with a requirement analysis performed on the feedback received from interviews with members of the Lighthouse for the Blind of Greece both of which lead to the proposal of a new implementation that pushes the state of the art.

Dynamic Crosswalk Scene Understanding for the Visually Impaired

Independent mobility poses a great challenge to the visually impaired individuals. This paper proposes a novel system to understand dynamic crosswalk scenes, which detects the key objects, such as crosswalk, vehicle, and pedestrian, and identifies pedestrian traffic light status. The indication of where and when to cross the road is provided to the visually impaired based on the crosswalk scene understanding. Our proposed system is implemented on a head-mounted mobile device (SensingAI G1) equipped with an Intel RealSense camera and a cellphone, and provides surrounding scene information to visually impaired individuals through audio signal. To validate the performance of the proposed system, we propose a crosswalk scene understanding dataset which contains three sub-datasets: a pedestrian traffic light dataset with 7447 images, a dataset of key objects on the crossroad with 1006 images and a crosswalk dataset with 3336 images. Extensive experiments demonstrated that the proposed system was robust and outperformed the state-of-the-art approaches. The experiment conducted with the visually impaired subjects shows that the system is practical useful.

Out on the streets - Crisis, opportunity and disabled people in the era of Covid-19: Reflections from the UK

Governments have responded to the Covid-19 crisis through various measures designed to reduce transmission and protect people judged to be at heightened risk. This paper explores the implications of such measures in the UK for disabled people, with a particular focus on measures designed to reduce and reshape the use of streets and public space. We divide UK measures into two broad categories. First, there are measures designed to reduce the use of streets and public spaces – e.g., rules requiring people to stay at home except in tightly prescribed circumstances and measures providing specific support (including food delivery and priority online shopping) for people designated as clinically extremely ‘vulnerable’. Second, there are measures designed to control the behaviour of people using streets and public space – e.g., rules on physical distancing and the use of face coverings. We explore the disability-related concerns associated with these types of measure. We also highlight the opportunities this crisis presents for embedding accessibility and inclusion more firmly into the fabric of our streets and call for renewed resistance to policies and practices shaped by ableist assumptions and attitudes.

Using Difference Images to Detect Pedestrian Signal Changes

This paper describes a method of using camera images to detect changes in the display status of pedestrian traffic signals. In much of the research previously done on signal detection, the color or shape of images or machine learning has been used to estimate the signal status. However, it is known that these methods are greatly affected by occlusion and changes in illumination. We propose a method of detecting, using multiple image sequences captured over time, changes in appearance that occur when a signal changes. If this method is used, the position and the status of the traffic light can be accurately detected as long as it appears in the image, even if its relative position or the lighting conditions in the area changes. In this paper, we first describe how pedestrian signals are seen when difference images are used, and we propose an algorithm for detecting when a signal changes. Then, the effectiveness of the proposed method is confirmed through verification tests.

Smartphone-Based Escalator Recognition for the Visually Impaired

It is difficult for visually impaired individuals to recognize escalators in everyday environments. If the individuals ride on escalators in the wrong direction, they will stumble on the steps. This paper proposes a novel method to assist visually impaired individuals in finding available escalators by the use of smartphone cameras. Escalators are recognized by analyzing optical flows in video frames captured by the cameras, and auditory feedback is provided to the individuals. The proposed method was implemented on an Android smartphone and applied to actual escalator scenes. The experimental results demonstrate that the proposed method is promising for helping visually impaired individuals use escalators.

Determining a Blind Pedestrian's Location and Orientation at Traffic Intersections

This paper describes recent progress on Crosswatch, a smartphone-based computer vision system developed by the authors for providing guidance to blind and visually impaired pedestrians at traffic intersections. One of Crosswatch's key capabilities is determining the user's location (with precision much better than what is obtainable by GPS) and orientation relative to the crosswalk markings in the intersection that he/she is currently standing at; this capability will be used to help him/her find important features in the intersection, such as walk lights, pushbuttons and crosswalks, and achieve proper alignment to these features. We report on two new contributions to Crosswatch: (a) experiments with a modified user interface, tested by blind volunteer participants, that makes it easier to acquire intersection images than with previous versions of Crosswatch; and (b) a demonstration of the system's ability to localize the user with precision better than what is obtainable by GPS, as well as an example of its ability to estimate the user's orientation.

SMARTPHONE-BASED CROSSWALK DETECTION AND LOCALIZATION FOR VISUALLY IMPAIRED PEDESTRIANS

This paper describes recent work on the "Crosswatch" project [7], which is a computer vision-based smartphone system developed for providing guidance to blind and visually impaired travelers at traffic intersections. A key function of Crosswatch is self-localization - the estimation of the user's location relative to the crosswalks in the current traffic intersection. Such information may be vital to users with low or no vision to ensure that they know which crosswalk they are about to enter, and are properly aligned and positioned relative to the crosswalk. However, while computer vision-based methods have been used [1,9,14] for finding crosswalks and helping blind travelers align themselves to them, these methods assume that the entire crosswalk pattern can be imaged in a single frame of video, which poses a significant challenge for a user who lacks enough vision to know where to point the camera so as to properly frame the crosswalk. In this paper we describe work in progress that tackles the problem of crosswalk detection and self-localization, building on recent work [8] describing techniques enabling blind and visually impaired users to acquire 360° image panoramas while turning in place on a sidewalk. The image panorama is converted to an aerial (overhead) view of the nearby intersection, centered on the location that the user is standing at, so as to facilitate matching with a template of the intersection obtained from Google Maps satellite imagery. The matching process allows crosswalk features to be detected and permits the estimation of the user's precise location relative to the crosswalk of interest. We demonstrate our approach on intersection imagery acquired by blind users, thereby establishing the feasibility of the approach.

Crosswatch: a System for Providing Guidance to Visually Impaired Travelers at Traffic Intersections

PURPOSE

This paper describes recent progress on the "Crosswatch" project, a smartphone-based system developed for providing guidance to blind and visually impaired travelers at traffic intersections. Building on past work on Crosswatch functionality to help the user achieve proper alignment with the crosswalk and read the status of walk lights to know when it is time to cross, we outline the directions Crosswatch is now taking to help realize its potential for becoming a practical system: namely, augmenting computer vision with other information sources, including geographic information systems (GIS) and sensor data, and inferring the user's location much more precisely than is possible through GPS alone, to provide a much larger range of information about traffic intersections to the pedestrian.

DESIGN/METHODOLOGY/APPROACH

The paper summarizes past progress on Crosswatch and describes details about the development of new Crosswatch functionalities. One such functionality, which is required for determination of the user's precise location, is studied in detail, including the design of a suitable user interface to support this functionality and preliminary tests of this interface with visually impaired volunteer subjects.

FINDINGS

The results of the tests of the new Crosswatch functionality demonstrate that the functionality is feasible in that it is usable by visually impaired persons.

RESEARCH LIMITATIONS/IMPLICATIONS

While the tests that were conducted of the new Crosswatch functionality are preliminary, the results of the tests have suggested several possible improvements, to be explored in the future.

PRACTICAL IMPLICATIONS

The results described in this paper suggest that the necessary technologies used by the Crosswatch system are rapidly maturing, implying that the system has an excellent chance of becoming practical in the near future.

ORIGINALITY/VALUE

The paper addresses an innovative solution to a key problem faced by blind and visually impaired travelers, which has the potential to greatly improve independent travel for these individuals.

[Healthcare "Apps" for Smartphones : Relief or toy for patients and the visual impaired?]

INTRODUCTION

Among the more than 1,500 "Apps" in the health sector numerous medical "Apps" and "Apps" for visually impaired persons are available.

METHODS

An Internet survey was performed to determine available medical "Apps" and evaluate their usability. The corresponding web pages were evaluated and the described "Apps" evaluated in a first analysis for the medical seriousness and usability. Identified "Apps" were entered again as key words to search for the most current and comprehensive assessment. In addition visual impaired persons possessing and using Smartphones were asked for their personal and subjective experiences and preference of selected "Apps".

RESULTS

The more than 50 "Apps" examined can be subdivided into different categories (A) stand-alone "Apps" and (B) global positioning system (GPS) driven navigation"Apps". Many "Apps" have only been available for a short time, still having some initial technical problems and are presently under further development. Medical "Apps" can support healthy and visually impaired people in many healthcare areas. A barrier-free access to these new technologies is essential for an unhindered utilization of "Apps" by visually impaired persons. Many "Apps" developed by and for visual impaired people received a high acceptance and popularity in practical applications.

CONCLUSION

The use of "Apps" in medical healthcare, especially for visually impaired persons, has a great potential to achieve a relief in the clinical provision for visually impaired persons with increasing distribution of smartphones and new technical developments.

(Computer) Vision without Sight

Computer vision holds great promise for helping persons with blindness or visual impairments (VI) to interpret and explore the visual world. To this end, it is worthwhile to assess the situation critically by understanding the actual needs of the VI population and which of these needs might be addressed by computer vision. This article reviews the types of assistive technology application areas that have already been developed for VI, and the possible roles that computer vision can play in facilitating these applications. We discuss how appropriate user interfaces are designed to translate the output of computer vision algorithms into information that the user can quickly and safely act upon, and how system-level characteristics affect the overall usability of an assistive technology. Finally, we conclude by highlighting a few novel and intriguing areas of application of computer vision to assistive technology.

Anti-Blur Feedback for Visually Impaired Users of Smartphone Cameras

A wide range of smartphone applications are emerging that employ image processing and computer vision algorithms to interpret the contents of images acquired by the phone's built-in camera, including applications that read product barcodes and recognize a variety of documents and other objects. However, almost all of these applications are designed for normally sighted users; a major barrier for visually impaired users (who might benefit greatly from such applications) is the difficulty of taking good-quality images. To overcome this barrier, this paper focuses on reducing the incidence of motion blur, caused by camera shake and other movements, which is a common cause of poor-quality, unusable images. We propose a simple technique for detecting camera shake, using the smartphone's built-in accelerometer (i.e. tilt sensor) to alert the user in real-time to any shake, providing feedback that enables him/her to hold the camera more steadily. A preliminary experiment with a blind iPhone user demonstrates the feasibility of the approach.