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Integrating Social Grouping for Multitarget Tracking Across Cameras in a CRF Model
Cross-referencing social media and public surveillance camera data for disaster response
Physical media (like surveillance cameras) and social media (like Instagram and Twitter) may both be useful in attaining on-the-ground information during an emergency or disaster situation. However, the intersection and reliability of both surveillance cameras and social media during a natural disaster are not fully understood. To address this gap, we tested whether social media is of utility when physical surveillance cameras went off-line during Hurricane Irma in 2017. Specifically, we collected and compared geo-tagged Instagram and Twitter posts in the state of Florida during times and in areas where public surveillance cameras went off-line. We report social media content and frequency and content to determine the utility for emergency managers or first responders during a natural disaster
SAM: The School Attachment Monitor
Secure Attachment relationships have been shown to minimise social and behavioural problems in children and boosts resilience to risks later on such as antisocial behaviour, heart pathologies, and suicide. Attachment assessment is an expensive and time-consuming process that is not often performed. The School Attachment Monitor (SAM) automates Attachment assessment to support expert assessors. It uses doll-play activities with the dolls augmented with sensors and the child's play recorded with cameras to provide data for assessment. Social signal processing tools are then used to analyse the data and to automatically categorize Attachment patterns. This paper presents the current SAM interactive prototype
Towards Egocentric Person Re-identification and Social Pattern Analysis
Wearable cameras capture a first-person view of the daily activities of the
camera wearer, offering a visual diary of the user behaviour. Detection of the
appearance of people the camera user interacts with for social interactions
analysis is of high interest. Generally speaking, social events, lifestyle and
health are highly correlated, but there is a lack of tools to monitor and
analyse them. We consider that egocentric vision provides a tool to obtain
information and understand users social interactions. We propose a model that
enables us to evaluate and visualize social traits obtained by analysing social
interactions appearance within egocentric photostreams. Given sets of
egocentric images, we detect the appearance of faces within the days of the
camera wearer, and rely on clustering algorithms to group their feature
descriptors in order to re-identify persons. Recurrence of detected faces
within photostreams allows us to shape an idea of the social pattern of
behaviour of the user. We validated our model over several weeks recorded by
different camera wearers. Our findings indicate that social profiles are
potentially useful for social behaviour interpretation
Who clicks there!: Anonymizing the photographer in a camera saturated society
In recent years, social media has played an increasingly important role in
reporting world events. The publication of crowd-sourced photographs and videos
in near real-time is one of the reasons behind the high impact. However, the
use of a camera can draw the photographer into a situation of conflict.
Examples include the use of cameras by regulators collecting evidence of Mafia
operations; citizens collecting evidence of corruption at a public service
outlet; and political dissidents protesting at public rallies. In all these
cases, the published images contain fairly unambiguous clues about the location
of the photographer (scene viewpoint information). In the presence of adversary
operated cameras, it can be easy to identify the photographer by also combining
leaked information from the photographs themselves. We call this the camera
location detection attack. We propose and review defense techniques against
such attacks. Defenses such as image obfuscation techniques do not protect
camera-location information; current anonymous publication technologies do not
help either. However, the use of view synthesis algorithms could be a promising
step in the direction of providing probabilistic privacy guarantees
Gated ‘communities’ - their lifestyle versus urban governance
Today there is a widespread fear of crime on a global scale. This can be seen as a response to social inequalities, social polarisation and the fragmentation of cities, which has been caused by neo-liberalism. Worldwide, an increasing number of higher income groups have looked to security measures, such as cameras, fences, walls and gates, to separate themselves from other people in the city. These physical measures, in combination with hired guards, replace the ‘older’ social control mechanisms, which are based on social cohesion within the community concerned. One may question whether those living in gated ‘communities’ indeed feel responsible for other urbanites. In other words, will such a hard closure (physically-marked segregation) lead to soft closure, reflected in social-cultural and political segregation. What is the impact of the lifestyle(s) of those living in gated communities on the dynamics of the city, urban identity and urban governance?
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