Abstract: The UK is leading in online retail and mobile
adoption. However, there is a dearth of information relating to mobile
apparel retail, and developing an understanding about consumer
browsing and purchase behaviour in m-retail channel would provide
apparel marketers, mobile website and app developers with the
necessary understanding of consumers’ needs. Despite the rapid
growth of mobile retail businesses, no published study has examined
shopping behaviour on fashion mobile apps and websites. A mixed method approach helped to understand why fashion
consumers prefer websites on smartphones, when diverse mobile
apps are also available. The following research methods were
employed: survey, eye-tracking experiments, observation, and
interview with retrospective think aloud. The mobile gaze tracking
device by SensoMotoric Instruments was used to understand
frustrations in navigation and other issues facing consumers in
mobile channel. This method helped to validate and compliment
other traditional user-testing approaches in order to optimize user
experience and enhance the development of mobile retail channel.
The study involved eight participants - females aged 18 to 35 years
old, who are existing mobile shoppers. The participants used the
Topshop mobile app and website on a smart phone to complete a task
according to a specified scenario leading to a purchase. The
comparative study was based on: duration and time spent at different
stages of the shopping journey, number of steps involved and product
pages visited, search approaches used, layout and visual clues, as
well as consumer perceptions and expectations. The results from the data analysis show significant differences in
consumer behaviour when using a mobile app or website on a smart
phone. Moreover, two types of problems were identified, namely
technical issues and human errors. Having a mobile app does not
guarantee success in satisfying mobile fashion consumers. The
differences in the layout and visual clues seem to influence the
overall shopping experience on a smart phone. The layout of search
results on the website was different from the mobile app. Therefore,
participants, in most cases, behaved differently on different
platforms. The number of product pages visited on the mobile app
was triple the number visited on the website due to a limited visibility
of products in the search results. Although, the data on traffic trends
held by retailers to date, including retail sector breakdowns for visits
and views, data on device splits and duration, might seem a valuable
source of information, it cannot explain why consumers visit many
product pages, stay longer on the website or mobile app, or abandon
the basket. A comprehensive list of pros and cons was developed by
highlighting issues for website and mobile app, and recommendations
provided. The findings suggest that fashion retailers need to be aware of
actual consumers’ behaviour on the mobile channel and their expectations in order to offer a seamless shopping experience. Added
to which is the challenge of retaining existing and acquiring new
customers. There seem to be differences in the way fashion
consumers search and shop on mobile, which need to be explored in
further studies.
Abstract: We present a dedicated video-based monitoring
system for quantification of patient’s attention to visual feedback
during robot assisted gait rehabilitation. Two different approaches for
eye gaze and head pose tracking are tested and compared. Several
metrics for assessment of patient’s attention are also presented.
Experimental results with healthy volunteers demonstrate that
unobtrusive video-based gaze tracking during the robot-assisted gait
rehabilitation is possible and is sufficiently robust for quantification
of patient’s attention and assessment of compliance with the
rehabilitation therapy.
Abstract: With advances in computer vision, non-contact gaze tracking systems are heading towards being much easier to operate and more comfortable for use, the technique proposed in this paper is specially designed for achieving these goals. For the convenience in operation, the proposal aims at the system with simple configuration which is composed of a fixed wide angle camera and dual infrared illuminators. Then in order to enhance the usability of the system based on single camera, a self-adjusting method which is called Real-time gaze Tracking Algorithm with head movement Compensation (RTAC) is developed for estimating the gaze direction under natural head movement and simplifying the calibration procedure at the same time. According to the actual evaluations, the average accuracy of about 1° is achieved over a field of 20×15×15 cm3.