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This article describes an algorithm that provides visual odometry estimates from sequential pairs of RGBD images. The key contribution of this article on RGBD odometry is that it provides both an odometry estimate and a covariance for the odometry parameters in real-time via a representative covariance matrix. Accurate, real-time parameter covariance is essential to effectively fuse odometry measurements...
Human controllers of Air-Traffic-Control (ATC) system is vital in ensuring flight safety and efficiency. In this paper, we strive to take advantage of visual tracking multi-targets within ATC surveillance videos to assist the human air traffic controllers making decisions more quickly and precisely. In this special case, it should be established as online real-time multi-object tracking (MOT) of a...
Measuring “how much the human is in the interaction” - the level of engagement - is instrumental in building effective interactive robots. Engagement, however, is a complex, multi-faceted cognitive mechanism that is only indirectly observable. This article formalizes with-me-ness as one of such indirect measures. With-me-ness, a concept borrowed from the field of Computer-Supported Collaborative Learning,...
Mitigation techniques employed by attackers has meant that traditional Network Intrusion Detection Systems (NIDS) are no longer able to reliably protect a network in the face of ever more sophisticated attacks. Security Information and Event Management (SIEM) systems monitor network systems by analyzing the logs they produce. In this paper, we propose a method of visualizing attacks by aggregating,...
Large display systems have been successfully applied in virtual reality domains because they can provide full sense of immersion through large visual space and high display resolution. However, only a few users can interact with these systems by using pen-like or marker-based devices. In addition, user experience and application mode are constrained in many areas. In this paper, we propose a novel...
This work is part of an application context, focused on the analysis of images flow acquired by a cameraembedded in a drone, controlled by a control station. Specifically, we are interested in the coupling vision-command, in order to develop a control system that allowsan autonomous navigation and operation of the UnmannedAerial Vehicle in complex environments where the use ofvisual sensors appears...
We consider the design of vision-based control algorithms for unmanned aerial vehicles (UAVs), so as to enable a UAV to autonomously follow a person. A new vision-based control architecture is proposed with the goals of 1) robustly following the user and 2) implementing following behaviors programmed by manipulation of visual patterns. This is achieved within a detection/tracking paradigm, where the...
After the Tohoku Earthquake on March 11, 2011, FUKUSHIMA prefecture has been afflicted by disasters like earthquake, tsunami and nuclear power accident, then decontamination work has been needed to be done in radioactive contamination area. A visual-servo type underwater vehicle system with binocular wide-angle lens has been developed and it has expanded the sphere for surveying submarine resources...
Nowadays, social networks are an essential part of modern life. People posts everything what happens with them and what happens around them. The amount of data, producing by social networks, increases dramatically every year and users more often post geo-tagged messages. It gives us more possibilities for visualization and analysis of social data, since we can be interested not only in the content...
In this study, real time classification of steady state-visual evoked potensials using the adaptive feedforward Neural Networks algorithm is proposed. The classification results is directly used to make a user able of controlling the directions (stop, forward, right, and left with stimuli frequencies of 7,5 10, 15, and 20 Hz, respectively) of a wheelchair based brain computer interface. The data was...
Understanding stakeholder perceptions and assessing the impact of campaigns are key questions of communication experts. Web intelligence platforms help to answer such questions, provided that they are scalable enough to analyze and visualize information flows from volatile online sources in real time. This paper presents a distributed architecture for aggregating Web content repositories from Web...
Both academia and organizations show great interest in streaming big data analytics - the process of extracting knowledge structures from continuous, high volume and high velocity continuous flow of data in a myriad of formats from a variety of real-time data sources. The challenge for organizations lies in being able to transform this deluge of data into instantaneous intelligence that can enable...
Curvature, the second-order directional derivative of an image, has been widely used for image interpolation. However, conventional curvature-based interpolation (CBI) methods employ a time-consuming post processing to reduce visual artifacts such as blurring and jagging caused by the inaccurate estimation of the local curvature. In this paper, a novel fast CBI method is proposed which can precisely...
In order to create or modify workflow model which is validated, it is good to support real-time trace and debug for data-intensive workflow model design tool. And, if it is possible to change variables of workflow instance, when workflow model trace or debug, it is very useful. So, we propose dynamic variables exchange method, and attempt to exchange variables on a data-intensive workflow modelling...
In this paper, we propose a novel interpolation algorithm for adapting the human visual system (HVS) and applying in real-time image upscaling. The defined statistical features are first computed in a local window of the low-resolution (LR) counterpart. Then the most correlated neighbours of a missing pixel in high-resolution (HR) image are adaptively selected based on local structural analysis for...
In this paper, we describe a method for Scale-Adaptive visual tracking using compressive sensing. Instead of using scale-invariant-features to estimate the object size every few frames, we use the compressed features at different scale then perform a second stage of classification to detect the best-fit scale. We describe the proposed mechanism of how we implement the Bayesian Classifier used in the...
This work presents an implementation of an augmented reality system that does not use fiducial markers for neither estimating the camera pose nor inserting a virtual object but natural marks such as corners of objects that are present in the scene. The system uses a RGB-D dataset for positioning the camera which moves with 6 DOF, for defining a work plane and for superimposing the object on the video...
Gaming and eSports have become increasingly popular and complex. For that reason, it is necessary that tournament hosts and game developers provide a great amount of meaningful information for their audiences. Data visualization tools and frameworks are of upmost importance since these provides means to accomplish this task. In this paper we propose GameVis, a framework designed to aid developers...
This paper presents a tool, called SAVE, developed on the ADOxx meta-modelling platform, to implement a dual approach to specify and verify the requirements for secure movements of processes in distributed mobile real-time systems. For specification, a process algebra, called ö-Calculus, was visualized to define the movements of processes on a conceptual geographical space. For verification, a first-order...
We demonstrate a near real-time service monitoring system for detecting and diagnosing issues from high-dimensional time series data. For detection, we have implemented a learning algorithm that constructs a hierarchy of detectors from data. It is scalable, does not require labelled examples of issues for learning, runs in near real-time, and identifles a subset of counter time series as being relevant...
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