82 research outputs found
Pedestrian Detection with Wearable Cameras for the Blind: A Two-way Perspective
Blind people have limited access to information about their surroundings,
which is important for ensuring one's safety, managing social interactions, and
identifying approaching pedestrians. With advances in computer vision, wearable
cameras can provide equitable access to such information. However, the
always-on nature of these assistive technologies poses privacy concerns for
parties that may get recorded. We explore this tension from both perspectives,
those of sighted passersby and blind users, taking into account camera
visibility, in-person versus remote experience, and extracted visual
information. We conduct two studies: an online survey with MTurkers (N=206) and
an in-person experience study between pairs of blind (N=10) and sighted (N=40)
participants, where blind participants wear a working prototype for pedestrian
detection and pass by sighted participants. Our results suggest that both of
the perspectives of users and bystanders and the several factors mentioned
above need to be carefully considered to mitigate potential social tensions.Comment: The 2020 ACM CHI Conference on Human Factors in Computing Systems
(CHI 2020
Enhanced DTLS with CoAP-based authentication scheme for the internet of things in healthcare application
RETRACTED ARTICLE: Internet of Things-Based Digital Video Intrusion for Intelligent Monitoring Approach
Computer Application in Game Map Path-Finding Based on Fuzzy Logic Dynamic Hierarchical Ant Colony Algorithm
A novel three-tier Internet of Things architecture with machine learning algorithm for early detection of heart diseases
Sports person psychological behaviour signal analysis during Thfeir activity session
Mental well-being is a significant resource for athletes about their success and growth. Athletes are now facing additional risk factors in mental health in the sporting community, such as heavy workout loads, rough races, and demanding lifestyles. The great difficulty is to diagnose conditions and acquire sport and exercise features that contribute to daily or long-term practice to detrimental emotional reactions. In this paper, the sports activity session monitoring system (SASMS) has been proposed using wearable devices and EEG signal by monitoring the sports person’s heart rate and psychological behaviour. The proposed SASMS mental-health analysis focused on model spectrum forms representing the best results, mental illness, and mental health. The paper’s key conclusions concerned with the athletes’ performance, occupational and personal advancement of athletes in mental health problems, strategies intended to track and sustain athletes’ mental health, and outflow of different mental illness types. This research’s findings provide the basis for implementing actions that promote a healthy emotional state in the sport to enhance activity and fitness.</jats:p
<i>Call for Special Issue Papers:</i> Multimedia Big Data Analytics for Engineering Education
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