You Can Touch This: Eleven Years and 258218 Images of Objects
alt.chi: See this, hear this, touch this, keep this
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Runge, Nina
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Schöning, Johannes
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Malaka, Rainer
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Frigo, Alberto
Extended Abstracts of the ACM CHI'16 Conference on Human Factors in
Computing Systems
2016-05-07
v.2
p.541-552
© Copyright 2016 ACM
Summary: Touch has become a central input modality for a wide variety of interactive
devices, most of our mobile devices are operated using touch. In addition to
interacting with digital artifacts, people touch and interact with many other
objects in their daily lives. We provide a unique photo dataset containing all
touched objects over the last 11 years. All photos were contributed by Alberto
Frigo, who was involved early on in the "Quantified Self" movement. He takes
photos of every object he touches with his dominant hand. We analyzed the
258,218 images with respect to the types objects, their distribution, and
related activities.
No more Autobahn!: Scenic Route Generation Using Googles Street View
Personalization
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Runge, Nina
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Samsonov, Pavel
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Degraen, Donald
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Schöning, Johannes
Proceedings of the 2016 International Conference on Intelligent User
Interfaces
2016-03-07
v.1
p.147-151
© Copyright 2016 ACM
Summary: Navigation systems allow drivers to find the shortest or fastest path
between two or multiple locations mostly using time or distance as input
parameters. Various researchers extended traditional route planning approaches
by taking into account the user's preferences, such as enjoying a coastal view
or alpine landscapes during a drive. Current approaches mainly rely on
volunteered geographic information (VGI), such as point of interest (POI) data
from OpenStreetMap, or social media data, such as geotagged photos from Flickr,
to generate scenic routes. While these approaches use proximity, distribution
or other spatial relationships of the data sets, they do not take into account
the actual view on specific route segments. In this paper, we propose Autobahn:
a system for generating scenic routes using Google Street View images to
classify route segments based on their visual characteristics enhancing the
driving experience. We show that this vision-based approach can complement
other approaches for scenic route planning and introduce a personalized scenic
route by aligning the characteristics of the route to the preferences of the
user.
MoviTouch: Mobile Movement Capability Configurations
Poster Session 2
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Smeddinck, Jan David
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Hey, Jorge
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Runge, Nina
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Herrlich, Marc
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Jacobsen, Christine
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Wolters, Jan
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Malaka, Rainer
Seventeenth International ACM SIGACCESS Conference on Computers and
Accessibility
2015-10-26
p.389-390
© Copyright 2015 ACM
Summary: Strong adaptability is a major requirement and challenge in the
physiotherapeutic use of motion-based games for health. For adaptation tool
development, tablets are a promising platform due to their similarity in
affordance compared to traditional clipboards. In a comparative study, we
examined three different input modalities on the tablet that allow for
configuring joint angles: direct-touch, classic interface components (e.g.
buttons and sliders), and a combination of both. While direct touch emerged as
the least preferable modality, the results highlight the benefits of the
combination of direct-touch and classic interface components as the most
accessible modality for configuring joint angle ranges. Furthermore, the
importance of configuring joint angles along three distinct axes and the
interesting use-case of configuration tools as communication support emerged.
Tags You Don't Forget: Gamified Tagging of Personal Images
Full Papers
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Runge, Nina
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Wenig, Dirk
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Zitzmann, Danny
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Malaka, Rainer
Proceedings of the 2015 International Conference on Entertainment Computing
2015-09-29
p.301-314
Keywords: gamification; image tagging; mobile devices
© Copyright 2015 IFIP
Summary: Mobile multi-purpose devices such as smartphones are progressively replacing
digital cameras; people use their smartphones as everyday companions and
increasingly take pictures in their daily life. Tagging is a way to organize
huge collections of photos but raises two challenges. First, tagging
(especially on mobile devices) is a boring task. Second, remembering the
assigned tags is important to find images with tags. We propose gamification
for more entertaining tagging. Most gamification approaches use crowd-based
assessments of good or bad tags, which is a good way to prevent cheating and to
not assign improper tags. However, it is not appropriate for personal images
because users don't want to share every image with the crowd. We developed and
evaluated two mobile apps with gamification elements to tag images, a
single-player and a multiplayer app. While both variants were more entertaining
than a simple tagging app, the single-player app helps users to remember
significant more tags.
Keep an eye on your photos: automatic image tagging on mobile devices
Poster Presentations
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Runge, Nina
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Wenig, Dirk
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Malaka, Rainer
Proceedings of 2014 Conference on Human-Computer Interaction with Mobile
Devices and Services
2014-09-23
p.513-518
© Copyright 2014 ACM
Summary: In this paper we present how to tag images automatically based on the image
and sensor data from a mobile device. We developed a system that computes
low-level tags using the image itself and meta data. Based on these tags and
previous user tags we learn high-level tags. With a
client-server-implementation we source out computational expensive algorithms
to recommend the tags as fast as possible. We show what are the best feature
extraction methods in combination with a machine learning technique to
recommend good tags.
