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

RGB-W: When Vision Meets Wireless

Inspired by the recent success of RGB-D cameras, we propose the enrichment of RGB data with an additional "quasi-free" modality, namely, the wireless signal (e.g., wifi or Bluetooth) emitted by individuals' cell phones, referred to as RGB-W. The received signal strength acts as a rough proxy for depth and a reliable cue on their identity. Although the measured signals are highly noisy (more than 2m average localization error), we demonstrate that the combination of visual and wireless data significantly improves the localization accuracy. We introduce a novel image-driven representation of wireless data which embeds all received signals onto a single image. We then indicate the ability of this additional data to (i) locate persons within a sparsity-driven framework and to (ii) track individuals with a new confidence measure on the data association problem. Our solution outperforms existing localization methods by a significant margin. It can be applied to the millions of currently installed RGB cameras to better analyze human behavior and offer the next generation of high-accuracy location-based services

Recent Advances in Indoor Localization Systems and Technologies

Despite the enormous technical progress seen in the past few years, the maturity of indoor localization technologies has not yet reached the level of GNSS solutions. The 23 selected papers in this book present the recent advances and new developments in indoor localization systems and technologies, propose novel or improved methods with increased performance, provide insight into various aspects of quality control, and also introduce some unorthodox positioning methods

Contextual Person Identification in Multimedia Data

We propose methods to improve automatic person identification, regardless of the visibility of a face, by integration of multiple cues including multiple modalities and contextual information. We propose a joint learning approach using contextual information from videos to improve learned face models. Further, we integrate additional modalities in a global fusion framework. We evaluate our approaches on a novel TV series data set, consisting of over 100 000 annotated faces

Stochastic filtering on mobile devices in complex dynamic environments

Gathering information, especially about the immediately surrounding world, is a central aspect of any smart device, whether it is a robot, a partially autonomous vehicle, or a mobile handheld device. The consequential use of electrical sensors always implies the need to filter the imperfect sensor data output in order to gain reliable information. While the challenge of perception and cognition in machines is not a new one, new technology constantly opens up new possibilities and challenges. This is stressed further by the advent of cheap sensor technology and the possibility to use a multitude of small sensors, with the simultaneous constraint of limited resources on mobile, battery-powered computing devices. In this work, stochastic methods are used to filter sensor data, which is gathered by mobile devices, to model the devices' location and eventually also relevant parts of their dynamic environment. This is done with a focus on online algorithms and computation on these mobile devices themselves, which implies limited available processing power and the necessity for computational efficiency. This dissertation's purpose is to impart a better understanding about the conception and design of stochastic filtering solutions, to propose localization algorithms beyond the current state of the art, and to show the use of simultaneous localization and mapping algorithms in the context of cooperatively estimating the surrounding world of a team of robots in a fast changing, dynamic environment. To achieve these goals, the concepts are depicted in multiple application scenarios, design choices and their implications systematically cover all aspects of sensing and estimation, and the proposed systems are evaluated in real-world experiments on humanoid robots and other mobile devices

Sensor fusion in smart camera networks for ambient intelligence

This short report introduces the topics of PhD research that was conducted on 2008-2013 and was defended on July 2013. The PhD thesis covers sensor fusion theory, gathers it into a framework with design rules for fusion-friendly design of vision networks, and elaborates on the rules through fusion experiments performed with four distinct applications of Ambient Intelligence

MATLAB

A well-known statement says that the PID controller is the "bread and butter" of the control engineer. This is indeed true, from a scientific standpoint. However, nowadays, in the era of computer science, when the paper and pencil have been replaced by the keyboard and the display of computers, one may equally say that MATLAB is the "bread" in the above statement. MATLAB has became a de facto tool for the modern system engineer. This book is written for both engineering students, as well as for practicing engineers. The wide range of applications in which MATLAB is the working framework, shows that it is a powerful, comprehensive and easy-to-use environment for performing technical computations. The book includes various excellent applications in which MATLAB is employed: from pure algebraic computations to data acquisition in real-life experiments, from control strategies to image processing algorithms, from graphical user interface design for educational purposes to Simulink embedded systems