Visual Overlay on OpenStreetMap Data to Support Spatial Exploration of Urban Environments

Increasing volumes of spatial data about urban areas are captured and made available via volunteered geographic information (VGI) sources, such as OpenStreetMap (OSM). Hence, new opportunities arise for regional exploration that can lead to improvements in the lives of citizens through spatial decision support. We believe that the VGI data of the urban environment could be used to present a constructive overview of the regional infrastructure with the advent of web technologies. Current location-based services provide general map-based information for the end users with conventional local search functionality, and hence, the presentation of the rich urban information is limited. In this work, we analyze the OSM data to classify the geo entities into consequential categories with facilities, landscape and land use distribution. We employ a visual overlay of heat map and interactive visualizations to present the regional characterization on OSM data classification. In the proposed interface, users are allowed to express a variety of spatial queries to exemplify their geographic interests. They can compare the characterization of urban areas with respect to multiple spatial dimensions of interest and can search for the most suitable region. The search experience is further enhanced via efficient optimization and interaction methods to support the decision making of end users. We report the end user acceptability and efficiency of the proposed system via usability studies and performance analysis comparison. Document type: Articl

PrivacEye: Privacy-Preserving Head-Mounted Eye Tracking Using Egocentric Scene Image and Eye Movement Features

Eyewear devices, such as augmented reality displays, increasingly integrate eye tracking but the first-person camera required to map a user's gaze to the visual scene can pose a significant threat to user and bystander privacy. We present PrivacEye, a method to detect privacy-sensitive everyday situations and automatically enable and disable the eye tracker's first-person camera using a mechanical shutter. To close the shutter in privacy-sensitive situations, the method uses a deep representation of the first-person video combined with rich features that encode users' eye movements. To open the shutter without visual input, PrivacEye detects changes in users' eye movements alone to gauge changes in the "privacy level" of the current situation. We evaluate our method on a first-person video dataset recorded in daily life situations of 17 participants, annotated by themselves for privacy sensitivity, and show that our method is effective in preserving privacy in this challenging setting.Comment: 10 pages, 6 figures, supplementary materia

Beyond Halo and Wedge: Visualizing out-of-view objects on head-mounted virtual and augmented reality devices

Head-mounted devices (HMDs) for Virtual and Augmented Reality (VR/AR) enable us to alter our visual perception of the world. However, current devices suffer from a limited field of view (FOV), which becomes problematic when users need to locate out of view objects (e.g., locating points-of-interest during sightseeing). To address this, we developed and evaluated in two studies HaloVR, WedgeVR, HaloAR and WedgeAR, which are inspired by usable 2D off-screen object visualization techniques (Halo, Wedge). While our techniques resulted in overall high usability, we found the choice of AR or VR impacts mean search time (VR: 2.25s, AR: 3.92s) and mean direction estimation error (VR: 21.85°, AR: 32.91°). Moreover, while adding more out-of-view objects significantly affects search time across VR and AR, direction estimation performance remains unaffected. We provide implications and discuss the challenges of designing for VR and AR HMDs

Technology literacy in poor infrastructure environments

While HCI for development (HCI4D) research has typically focused on technological practices of poor and low-literate communities, little research has addressed how technology literate individuals living in a poor infrastructure environment use technology. Our work fills this gap by focusing on Lebanon, a country with longstanding political instability, and the wayfinding issues there stemming from missing street signs and names, a poor road infrastructure, and a non-standardized addressing system. We examine the relationship between technology literate individuals' navigation and direction giving strategies and their usage of current digital navigation aids. Drawing on an interview study (N=12) and a web survey (N=85), our findings show that while these individuals rely on mapping services and WhatsApp's share location feature to aid wayfinding, many technical and cultural problems persist that are currently resolved through social querying. We discuss our results in light of problems that any map user encounters in poor infrastructure environments

Measuring, Understanding, and Classifying News Media Sympathy on Twitter after Crisis Events

This paper investigates bias in coverage between Western and Arab media on Twitter after the November 2015 Beirut and Paris terror attacks. Using two Twitter datasets covering each attack, we investigate how Western and Arab media differed in coverage bias, sympathy bias, and resulting information propagation. We crowdsourced sympathy and sentiment labels for 2,390 tweets across four languages (English, Arabic, French, German), built a regression model to characterize sympathy, and thereafter trained a deep convolutional neural network to predict sympathy. Key findings show: (a) both events were disproportionately covered (b) Western media exhibited less sympathy, where each media coverage was more sympathetic towards the country affected in their respective region (c) Sympathy predictions supported ground truth analysis that Western media was less sympathetic than Arab media (d) Sympathetic tweets do not spread any further. We discuss our results in light of global news flow, Twitter affordances, and public perception impact.Comment: In Proc. CHI 2018 Papers program. Please cite: El Ali, A., Stratmann, T., Park, S., Sch\"oning, J., Heuten, W. & Boll, S. (2018). Measuring, Understanding, and Classifying News Media Sympathy on Twitter after Crisis Events. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI '18). ACM, New York, NY, USA. DOI: https://doi.org/10.1145/3173574.317413

RadialLight: Exploring radial peripheral LEDs for directional cues in head-mounted displays

Current head-mounted displays (HMDs) for Virtual Reality (VR) and Augmented Reality (AR) have a limited field-of-view (FOV). This limited FOV further decreases the already restricted human visual range and amplifies the problem of objects going out of view. Therefore, we explore the utility of augmenting HMDs with RadialLight, a peripheral light display implemented as 18 radially positioned LEDs around each eye to cue direction towards out-of-view objects. We first investigated direction estimation accuracy of multi-colored cues presented on one versus two eyes. We then evaluated direction estimation accuracy and search time performance for locating out-of-view objects in two representative 360° video VR scenarios. Key findings show that participants could not distinguish between LED cues presented to one or both eyes simultaneously, participants estimated LED cue direction within a maximum 11.8° average deviation, and out-of-view objects in less distracting scenarios were selected faster. Furthermore, we provide implications for building peripheral HMDs

Investigations on Container Ship Berthing from the Pilot’s Perspective: Accident Analysis, Ethnographic Study, and Online Survey

In recent years, container ships have had to transport more and more goods due to constantly growing demand. Therefore, the container ships for carrying these goods are growing in size, while the harbors fall short in adapting to these changes. As a result, the berthing of these container ships in harbors has become more challenging for harbor pilots. In this work, we identify problems and risks with which pilots are confronted during the berthing process. First, we analyzed approximately 1500 accident reports from six different transportation safety authorities and identified their major causes. Second, we conducted an ethnographic study with harbor pilots in Hamburg to observe their actions. Third, we gained more specific insights on pilots environments and communications through an online survey of 30 harbor pilots from different European countries. We conclude our work with recommendations on how to reduce problems and risks during berthing of container vessels

To Beep or Not to Beep? Evaluating Modalities for Multimodal ICU Alarms

Technology plays a prominent role in intensive care units (ICU), with a variety of sensors monitoring both patients and devices. A serious problem exists, however, that can reduce the sensors’ effectiveness. When important values exceed or fall below a certain threshold or sensors lose their signal, up to 350 alarms per patient a day are issued. These frequent alarms are audible in several locations on the ICU, resulting in a massive cognitive load for ICU nurses, as they must evaluate and acknowledge each alarm. “Alarm fatigue” sets in, a desensitization and delayed response time for alarms that can have severe consequences for patients and nurses. To counteract the acoustic load on ICUs, we designed and evaluated personal multimodal alarms for a wearable alarm system (WAS). The result was a lower response time and higher ratings on suitability and feasibility, as well as a lower annoyance level, compared to acoustic alarms. We find that multimodal alarms are a promising new approach to alert ICU nurses, reduce cognitive load, and avoid alarm fatigue