DocumentCode :
19431
Title :
Wearable Cameras: Identifying Healthy Transportation Choices
Author :
Doherty, Andrew ; Kelly, Patrick ; Foster, C.
Author_Institution :
Centre for Sensor Web Technol., Dublin City Univ., Dublin, Ireland
Volume :
12
Issue :
1
fYear :
2013
fDate :
Jan.-Mar. 2013
Firstpage :
44
Lastpage :
47
Abstract :
Traditionally, health researchers have used large-scale travel surveys to measure existing travel behavior and identify the determinants driving it. However, such surveys rely on self-reporting, which can be unreliable. Here, the authors discuss using wearable cameras that capture first-person point-of-view images to help objectively identify the duration, frequency, and mode of journeys and reveal potential errors inherent in self-reporting. Their approach could ultimately lead to a better understanding of the environments offering individuals opportunities to engage in more active forms of transportation. This column is part of a special issue on transit and transport.
Keywords :
cameras; health care; image segmentation; traffic engineering computing; transportation; driving; first-person point-of-view images; healthy transportation choices; wearable cameras; Behavioral science; Image segmentation; Pervasive computing; Public healthcare; Transportation; Travel services; Wearable computers; SenseCam; transportation; wearable cameras; wearable computing;
fLanguage :
English
Journal_Title :
Pervasive Computing, IEEE
Publisher :
ieee
ISSN :
1536-1268
Type :
jour
DOI :
10.1109/MPRV.2013.21
Filename :
6415933
Link To Document :
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