12,084 research outputs found
A generic framework for video understanding applied to group behavior recognition
This paper presents an approach to detect and track groups of people in
video-surveillance applications, and to automatically recognize their behavior.
This method keeps track of individuals moving together by maintaining a spacial
and temporal group coherence. First, people are individually detected and
tracked. Second, their trajectories are analyzed over a temporal window and
clustered using the Mean-Shift algorithm. A coherence value describes how well
a set of people can be described as a group. Furthermore, we propose a formal
event description language. The group events recognition approach is
successfully validated on 4 camera views from 3 datasets: an airport, a subway,
a shopping center corridor and an entrance hall.Comment: (20/03/2012
Eavesdropping Whilst You're Shopping: Balancing Personalisation and Privacy in Connected Retail Spaces
Physical retailers, who once led the way in tracking with loyalty cards and
`reverse appends', now lag behind online competitors. Yet we might be seeing
these tables turn, as many increasingly deploy technologies ranging from simple
sensors to advanced emotion detection systems, even enabling them to tailor
prices and shopping experiences on a per-customer basis. Here, we examine these
in-store tracking technologies in the retail context, and evaluate them from
both technical and regulatory standpoints. We first introduce the relevant
technologies in context, before considering privacy impacts, the current
remedies individuals might seek through technology and the law, and those
remedies' limitations. To illustrate challenging tensions in this space we
consider the feasibility of technical and legal approaches to both a) the
recent `Go' store concept from Amazon which requires fine-grained, multi-modal
tracking to function as a shop, and b) current challenges in opting in or out
of increasingly pervasive passive Wi-Fi tracking. The `Go' store presents
significant challenges with its legality in Europe significantly unclear and
unilateral, technical measures to avoid biometric tracking likely ineffective.
In the case of MAC addresses, we see a difficult-to-reconcile clash between
privacy-as-confidentiality and privacy-as-control, and suggest a technical
framework which might help balance the two. Significant challenges exist when
seeking to balance personalisation with privacy, and researchers must work
together, including across the boundaries of preferred privacy definitions, to
come up with solutions that draw on both technology and the legal frameworks to
provide effective and proportionate protection. Retailers, simultaneously, must
ensure that their tracking is not just legal, but worthy of the trust of
concerned data subjects.Comment: 10 pages, 1 figure, Proceedings of the PETRAS/IoTUK/IET Living in the
Internet of Things Conference, London, United Kingdom, 28-29 March 201
Data Mining in Electronic Commerce
Modern business is rushing toward e-commerce. If the transition is done
properly, it enables better management, new services, lower transaction costs
and better customer relations. Success depends on skilled information
technologists, among whom are statisticians. This paper focuses on some of the
contributions that statisticians are making to help change the business world,
especially through the development and application of data mining methods. This
is a very large area, and the topics we cover are chosen to avoid overlap with
other papers in this special issue, as well as to respect the limitations of
our expertise. Inevitably, electronic commerce has raised and is raising fresh
research problems in a very wide range of statistical areas, and we try to
emphasize those challenges.Comment: Published at http://dx.doi.org/10.1214/088342306000000204 in the
Statistical Science (http://www.imstat.org/sts/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Realising context-sensitive mobile messaging
Mobile technologies aim to assist people as they move from place to place going about their daily work and social routines. Established and very popular mobile technologies include short-text messages and multimedia messages with newer growing technologies including Bluetooth mobile data transfer protocols and mobile web access.Here we present new work which combines all of the above technologies to fulfil some of the predictions for future context aware messaging. We present a context sensitive mobile messaging system which derives context in the form of physical locations through location sensing and the co-location of people through Bluetooth familiarity
Evaluating indoor positioning systems in a shopping mall : the lessons learned from the IPIN 2018 competition
The Indoor Positioning and Indoor Navigation (IPIN) conference holds an annual competition in which indoor localization systems from different research groups worldwide are evaluated empirically. The objective of this competition is to establish a systematic evaluation methodology with rigorous metrics both for real-time (on-site) and post-processing (off-site) situations, in a realistic environment unfamiliar to the prototype developers. For the IPIN 2018 conference, this competition was held on September 22nd, 2018, in Atlantis, a large shopping mall in Nantes (France). Four competition tracks (two on-site and two off-site) were designed. They consisted of several 1 km routes traversing several floors of the mall. Along these paths, 180 points were topographically surveyed with a 10 cm accuracy, to serve as ground truth landmarks, combining theodolite measurements, differential global navigation satellite system (GNSS) and 3D scanner systems. 34 teams effectively competed. The accuracy score corresponds to the third quartile (75th percentile) of an error metric that combines the horizontal positioning error and the floor detection. The best results for the on-site tracks showed an accuracy score of 11.70 m (Track 1) and 5.50 m (Track 2), while the best results for the off-site tracks showed an accuracy score of 0.90 m (Track 3) and 1.30 m (Track 4). These results showed that it is possible to obtain high accuracy indoor positioning solutions in large, realistic environments using wearable light-weight sensors without deploying any beacon. This paper describes the organization work of the tracks, analyzes the methodology used to quantify the results, reviews the lessons learned from the competition and discusses its future
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