Image charge inclusion in the dielectric sphere revisited

Van Siclen (1988 Am. J. Phys. 56 1142) reported a curious property of a dielectric sphere in the field of an external point charge: the field outside the sphere generated by the combination of the original charge exterior and the Kelvin image charge interior to the sphere is independent of the permittivity of the sphere. In this paper,we simplify and correct the original derivation and give a detailed analysis of the sources of the field. We also present various checks for the theory, providing instructive exercises for advanced undergraduates

Derivations of relativistic force transformation equations

The correct general form of relativistic transformation equations for the three-vector force is derived without using four-vectors, via the relativistic Newton's second law. The four-vector approach to the problem is also presented. The derivations extend or rectify previous derivations

An extension of the Kelvin image theory to the conducting heaviside ellipsoid

The Kelvin image theory for a conducting sphere is extended to the case of a conducting oblate spheroid in uniform motion along its axis of revolution (a Heaviside ellipsoid) using the well-known method provided by Special Relativity. The results derived are checked in various ways

A route identification algorithm for assisted living applications fusing WLAN, GPS and image matching data

This paper addresses the automatic identification of often traversedroutes for assisted living applications using WLAN technology in addition to other modalities. This problem is complicated by a number of factors, including the changing and noisy nature of the WLAN channel, the need to track users seamlessly in both indoor and outdoor environments, the need for robustness to slight deviations in the precise path taken, and speed, along a route. In this work commonly traversed routes are identified by clustering based on sensed data, two of which take the form of wireless signals: GPS and WLAN. The latter is particularly important as it can be used both indoors and outdoors. In addition an efficient image matching algorithm is implemented to process data from images automatically taken along the route. In this work a finite number of routes were identified within the DCU campus. Each route was traversed many times over a period of 6 weeks and data sequences collected automatically on each occasion. Each such traversal of a route is referred to as a trip in what follows. Section (2) outlines the use of Multidimensional Time Warping in order to automatically cluster trips corresponding to specific routes based on wireless and image data sensed on each trip. Section (3) outlines the manner in which data was sensed and presents clustering results for each modality individually as well as results based on a fusion of the data

Dual-sensor fusion for indoor user localisation

In this paper we address the automatic identification of in- door locations using a combination of WLAN and image sensing. Our motivation is the increasing prevalence of wear- able cameras, some of which can also capture WLAN data. We propose to use image-based and WLAN-based localisa- tion individually and then fuse the results to obtain better performance overall. We demonstrate the effectiveness of our fusion algorithm for localisation to within a 8.9m2 room on very challenging data both for WLAN and image-based algorithms. We envisage the potential usefulness of our ap- proach in a range of ambient assisted living applications

Indoor localisation based on fusing WLAN and image data

In this paper we address the automatic identification of indoor locations using a combination of WLAN and image sensing. We demonstrate the effectiveness of combining the strengths of these two complementary modalities for very chal- lenging data. We describe a fusion approach that allows localising to a specific office within a building to a high degree of precision or to a location within that office with reasonable precision. As it can be orientated towards the needs and capabilities of a user based on context the method becomes useful for ambient assisted living applications

User tracking using a wearable camera

Abstract—This paper addresses automatic indoor user tracking based on fusion of WLAN and image sensing. Our motivation is the increasing prevalence of wearable cameras, some of which can also capture WLAN data. We propose a novel tracking method that can be employed when using image-based, WLAN-based and fusion-based approach only. The effectiveness of combining the strengths of these two complementary modalities is demonstrated for a very challenging data

Using SenseCam images in a multimodal fusion framework for route detection and localisation

Problem of structuring location data is solved by proposing a framework for classifying the data into often-traversed routes. It does not rely on any one source of location information, but can fuse data from multimodal localisation sources: SenseCam images, GPS data and WLAN signal strengths

A hybrid method for indoor user localisation

In this work we describe an approach to indoor user localisation by combining image-based and RF-based methods and compare this new approach to prior work. This paper details a new algorithm for indoor user localisation, demonstrating more effective user localisation than prior approaches and therefore presents the next step in combining two different technologies for localisation in indoor type environments

Multimodal identification of journeys

Due to the ubiquity of localisation technology, users now have the ability to keep a record of their own location, as a kind of ‘location diary’. Such a large collection of data can become unmanageable without some way to structure that data to make it useful and searchable. We address this problem of structuring location data by proposing a framework for classifying the data into often-traversed routes. In this work, commonly traversed routes are identified with clusters based on sensed data. Our framework does not rely on any one source of location information, but can fuse data from multimodal localisation sources. We demonstrate the effectiveness of our algorithm by examining the combination of GPS, wireless signal strength readings and image-matching on very challenging data in a variety of environmental conditions. By fusing these three modalities we obtained better performance than any individual or combination of two modalities. As it can be orientated towards the needs and capabilities of the user based on context, this method becomes useful for some ambient assisted living applications