5,688 research outputs found
Living Without a Mobile Phone: An Autoethnography
This paper presents an autoethnography of my experiences living without a
mobile phone. What started as an experiment motivated by a personal need to
reduce stress, has resulted in two voluntary mobile phone breaks spread over
nine years (i.e., 2002-2008 and 2014-2017). Conducting this autoethnography is
the means to assess if the lack of having a phone has had any real impact in my
life. Based on formative and summative analyses, four meaningful units or
themes were identified (i.e., social relationships, everyday work, research
career, and location and security), and judged using seven criteria for
successful ethnography from existing literature. Furthermore, I discuss factors
that allow me to make the choice of not having a mobile phone, as well as the
relevance that the lessons gained from not having a mobile phone have on the
lives of people who are involuntarily disconnected from communication
infrastructures.Comment: 12 page
RGB-D-based Action Recognition Datasets: A Survey
Human action recognition from RGB-D (Red, Green, Blue and Depth) data has
attracted increasing attention since the first work reported in 2010. Over this
period, many benchmark datasets have been created to facilitate the development
and evaluation of new algorithms. This raises the question of which dataset to
select and how to use it in providing a fair and objective comparative
evaluation against state-of-the-art methods. To address this issue, this paper
provides a comprehensive review of the most commonly used action recognition
related RGB-D video datasets, including 27 single-view datasets, 10 multi-view
datasets, and 7 multi-person datasets. The detailed information and analysis of
these datasets is a useful resource in guiding insightful selection of datasets
for future research. In addition, the issues with current algorithm evaluation
vis-\'{a}-vis limitations of the available datasets and evaluation protocols
are also highlighted; resulting in a number of recommendations for collection
of new datasets and use of evaluation protocols
Understanding Context to Capture when Reconstructing Meaningful Spaces for Remote Instruction and Connecting in XR
Recent technological advances are enabling HCI researchers to explore
interaction possibilities for remote XR collaboration using high-fidelity
reconstructions of physical activity spaces. However, creating these
reconstructions often lacks user involvement with an overt focus on capturing
sensory context that does not necessarily augment an informal social
experience. This work seeks to understand social context that can be important
for reconstruction to enable XR applications for informal instructional
scenarios. Our study involved the evaluation of an XR remote guidance prototype
by 8 intergenerational groups of closely related gardeners using
reconstructions of personally meaningful spaces in their gardens. Our findings
contextualize physical objects and areas with various motivations related to
gardening and detail perceptions of XR that might affect the use of
reconstructions for remote interaction. We discuss implications for user
involvement to create reconstructions that better translate real-world
experience, encourage reflection, incorporate privacy considerations, and
preserve shared experiences with XR as a medium for informal intergenerational
activities.Comment: 26 pages, 5 figures, 4 table
GUI system for Elders/Patients in Intensive Care
In the old age, few people need special care if they are suffering from
specific diseases as they can get stroke while they are in normal life routine.
Also patients of any age, who are not able to walk, need to be taken care of
personally but for this, either they have to be in hospital or someone like
nurse should be with them for better care. This is costly in terms of money and
man power. A person is needed for 24x7 care of these people. To help in this
aspect we purposes a vision based system which will take input from the patient
and will provide information to the specified person, who is currently may not
in the patient room. This will reduce the need of man power, also a continuous
monitoring would not be needed. The system is using MS Kinect for gesture
detection for better accuracy and this system can be installed at home or
hospital easily. The system provides GUI for simple usage and gives visual and
audio feedback to user. This system work on natural hand interaction and need
no training before using and also no need to wear any glove or color strip.Comment: In proceedings of the 4th IEEE International Conference on
International Technology Management Conference, Chicago, IL USA, 12-15 June,
201
MetaSpace II: Object and full-body tracking for interaction and navigation in social VR
MetaSpace II (MS2) is a social Virtual Reality (VR) system where multiple
users can not only see and hear but also interact with each other, grasp and
manipulate objects, walk around in space, and get tactile feedback. MS2 allows
walking in physical space by tracking each user's skeleton in real-time and
allows users to feel by employing passive haptics i.e., when users touch or
manipulate an object in the virtual world, they simultaneously also touch or
manipulate a corresponding object in the physical world. To enable these
elements in VR, MS2 creates a correspondence in spatial layout and object
placement by building the virtual world on top of a 3D scan of the real world.
Through the association between the real and virtual world, users are able to
walk freely while wearing a head-mounted device, avoid obstacles like walls and
furniture, and interact with people and objects. Most current virtual reality
(VR) environments are designed for a single user experience where interactions
with virtual objects are mediated by hand-held input devices or hand gestures.
Additionally, users are only shown a representation of their hands in VR
floating in front of the camera as seen from a first person perspective. We
believe, representing each user as a full-body avatar that is controlled by
natural movements of the person in the real world (see Figure 1d), can greatly
enhance believability and a user's sense immersion in VR.Comment: 10 pages, 9 figures. Video:
http://living.media.mit.edu/projects/metaspace-ii
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