A Radio-Inertial Localization and Tracking System with BLE Beacons Prior Maps

© 2018 IEEE. In this paper, we develop a system for the low-cost indoor localization and tracking problem using radio signal strength indicator, Inertial Measurement Unit (IMU), and magnetometer sensors. We develop a novel and simplified probabilistic IMU motion model as the proposal distribution of the sequential Monte-Carlo technique to track the robot trajectory. Our algorithm can globally localize and track a robot with a priori unknown location, given an informative prior map of the Bluetooth Low Energy (BLE) beacons. Also, we formulate the problem as an optimization problem that serves as the Backend of the algorithm mentioned above (Front-end). Thus, by simultaneously solving for the robot trajectory and the map of BLE beacons, we recover a continuous and smooth trajectory of the robot, corrected locations of the BLE beacons, and the time-varying IMU bias. The evaluations achieved using hardware show that through the proposed closed-loop system the localization performance can be improved; furthermore, the system becomes robust to the error in the map of beacons by feeding back the optimized map to the Front-end

VSCAN: An Enhanced Video Summarization using Density-based Spatial Clustering

In this paper, we present VSCAN, a novel approach for generating static video summaries. This approach is based on a modified DBSCAN clustering algorithm to summarize the video content utilizing both color and texture features of the video frames. The paper also introduces an enhanced evaluation method that depends on color and texture features. Video Summaries generated by VSCAN are compared with summaries generated by other approaches found in the literature and those created by users. Experimental results indicate that the video summaries generated by VSCAN have a higher quality than those generated by other approaches.Comment: arXiv admin note: substantial text overlap with arXiv:1401.3590 by other authors without attributio

Supporting users tasks with personal information management and web forms augmentation

Currently, many tasks performed on the Web prompt users to provide personal information through forms. Despite the fact that most users are familiarized with this kind of interaction technique, the use of Web forms is not always straightforward. Indeed, some users might need assistance to understand labels and complex data format required to fill in form fields that, quite often, vary from a Web site to another even when requesting similar data. Filling in forms can be tedious and repetitive as many Web sites request similar information. In this work we analyze user's interactions with Web forms and propose an approach for enhancing Web forms using client-side adaptation techniques in order to assist users to fill in Web forms. As the use of Web forms is closely related to the management of personal information our approach includes the support for data exchange between user's personal information management systems (PIMs) and third-party Web forms. The approach is illustrated by a set of client-side adaptation tools and a pervasive Personal Information Management Systems called PIMI.Publicado en Lecture Notes in Computer Science book series (vol. 7387).Laboratorio de Investigación y Formación en Informática Avanzad

COMPUTER NETWORKS ISDN SYSTEMS

The phenomenal interest and growth of the World Wide Web as an application server has pushed the Web model to its limits. Specifically, the Web offers limited interactivity and versatility as a platform for networked applications. One major challenge for the HCI community is to determine how to improve the human-computer interface for Web-based applications. This paper focuses on a significant Web deficiency – supporting truly interactive and dynamic form-based input. We propose a well-worked form interaction abstraction that alleviates this Web deficiency. We describe how the abstraction is seamlessly integrated into the Web framework by leveraging on the virtues of the Web and fitting within the interaction and usage model of the Web. © 1997 Published by Elsevier Science B.V

NewsFlash: Adaptive TV News Delivery on the Web

Abstract. In this paper we present NewsFlash, an adaptive search system that assists a searcher to efficiently search a library of stored TV news reports. The system automatically summarises the closed-caption subtitles embedded in the TV broadcasts and selects appropriate sentences to best describe report content in respect to the searcher’s query. During interaction the system selects useful terms from these summaries and uses these terms to update the display and potentially update a stored searcher profile. We evaluate the worth of our approach with real searchers and realistic information seeking scenarios. A novel means of testing the worth of a permanent profile of searchers ’ general interests is also proposed. Our results show that the adaptive techniques we propose can work well in multimedia search environments.