14,591 research outputs found
The Evolution of First Person Vision Methods: A Survey
The emergence of new wearable technologies such as action cameras and
smart-glasses has increased the interest of computer vision scientists in the
First Person perspective. Nowadays, this field is attracting attention and
investments of companies aiming to develop commercial devices with First Person
Vision recording capabilities. Due to this interest, an increasing demand of
methods to process these videos, possibly in real-time, is expected. Current
approaches present a particular combinations of different image features and
quantitative methods to accomplish specific objectives like object detection,
activity recognition, user machine interaction and so on. This paper summarizes
the evolution of the state of the art in First Person Vision video analysis
between 1997 and 2014, highlighting, among others, most commonly used features,
methods, challenges and opportunities within the field.Comment: First Person Vision, Egocentric Vision, Wearable Devices, Smart
Glasses, Computer Vision, Video Analytics, Human-machine Interactio
Surveying human habit modeling and mining techniques in smart spaces
A smart space is an environment, mainly equipped with Internet-of-Things (IoT) technologies, able to provide services to humans, helping them to perform daily tasks by monitoring the space and autonomously executing actions, giving suggestions and sending alarms. Approaches suggested in the literature may differ in terms of required facilities, possible applications, amount of human intervention required, ability to support multiple users at the same time adapting to changing needs. In this paper, we propose a Systematic Literature Review (SLR) that classifies most influential approaches in the area of smart spaces according to a set of dimensions identified by answering a set of research questions. These dimensions allow to choose a specific method or approach according to available sensors, amount of labeled data, need for visual analysis, requirements in terms of enactment and decision-making on the environment. Additionally, the paper identifies a set of challenges to be addressed by future research in the field
A Data Fusion System to Study Synchronization in Social Activities
As the world population gets older, the healthcare system must be adapted,
among others by providing continuous health monitoring at home and in the city.
The social activities have a significant role in everyone health status. Hence,
this paper proposes a system to perform a data fusion of signals sampled on
several subjects during social activities. This study implies the time
synchronization of data coming from several sensors whether these are embedded
on people or integrated in the environment. The data fusion is applied to
several experiments including physical, cognitive and rest activities, with
social aspects. The simultaneous and continuous analysis of four subjects
cardiac activity and GPS coordinates provides a new way to distinguish
different collaborative activities comparing the measurements between the
subjects and along time.Comment: Healthcom 201
Derandomized Distributed Multi-resource Allocation with Little Communication Overhead
We study a class of distributed optimization problems for multiple shared
resource allocation in Internet-connected devices. We propose a derandomized
version of an existing stochastic additive-increase and multiplicative-decrease
(AIMD) algorithm. The proposed solution uses one bit feedback signal for each
resource between the system and the Internet-connected devices and does not
require inter-device communication. Additionally, the Internet-connected
devices do not compromise their privacy and the solution does not dependent on
the number of participating devices. In the system, each Internet-connected
device has private cost functions which are strictly convex, twice continuously
differentiable and increasing. We show empirically that the long-term average
allocations of multiple shared resources converge to optimal allocations and
the system achieves minimum social cost. Furthermore, we show that the proposed
derandomized AIMD algorithm converges faster than the stochastic AIMD algorithm
and both the approaches provide approximately same solutions
Genetic Programming for Smart Phone Personalisation
Personalisation in smart phones requires adaptability to dynamic context
based on user mobility, application usage and sensor inputs. Current
personalisation approaches, which rely on static logic that is developed a
priori, do not provide sufficient adaptability to dynamic and unexpected
context. This paper proposes genetic programming (GP), which can evolve program
logic in realtime, as an online learning method to deal with the highly dynamic
context in smart phone personalisation. We introduce the concept of
collaborative smart phone personalisation through the GP Island Model, in order
to exploit shared context among co-located phone users and reduce convergence
time. We implement these concepts on real smartphones to demonstrate the
capability of personalisation through GP and to explore the benefits of the
Island Model. Our empirical evaluations on two example applications confirm
that the Island Model can reduce convergence time by up to two-thirds over
standalone GP personalisation.Comment: 43 pages, 11 figure
On environments as systemic exoskeletons: Crosscutting optimizers and antifragility enablers
Classic approaches to General Systems Theory often adopt an individual
perspective and a limited number of systemic classes. As a result, those
classes include a wide number and variety of systems that result equivalent to
each other. This paper introduces a different approach: First, systems
belonging to a same class are further differentiated according to five major
general characteristics. This introduces a "horizontal dimension" to system
classification. A second component of our approach considers systems as nested
compositional hierarchies of other sub-systems. The resulting "vertical
dimension" further specializes the systemic classes and makes it easier to
assess similarities and differences regarding properties such as resilience,
performance, and quality-of-experience. Our approach is exemplified by
considering a telemonitoring system designed in the framework of Flemish
project "Little Sister". We show how our approach makes it possible to design
intelligent environments able to closely follow a system's horizontal and
vertical organization and to artificially augment its features by serving as
crosscutting optimizers and as enablers of antifragile behaviors.Comment: Accepted for publication in the Journal of Reliable Intelligent
Environments. Extends conference papers [10,12,15]. The final publication is
available at Springer via http://dx.doi.org/10.1007/s40860-015-0006-
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