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In this paper, we investigate the prediction of mobile MIMO channels with varying multipath parameters. Based on the PAST algorithm, we propose a multidimensional adaptive ESPRIT approach for jointly tracking the evolution of the Doppler frequencies and spatial directions of arrival and departure of the propagation paths. Future states of the channel are predicted using the last estimate of the propagation...
In this paper, a cost efficient fusion scheme, Ubiquitous Tracking with Motion and Location Sensor (UTMLS), is proposed for the accurate localization and tracking in mixed GPS-friendly, GPS-challenging, and GPS-denied scenario. The proposed drift-reduction method in UTMLS addresses the cumulating error issue in the indoor tracking with the consumer grade motion sensor. The proposed hypothesis test...
This paper is concerned with the problem of attitude estimation for a wrist-worn motion sensor equipped with a 3-axis gyroscope and a 3-axis accelerometer. In the absence of motion and the with the arm in its natural resting state, the attitude is unobservable because the accelerometer's measurement of the gravity vector alone can not distinguish between configurations of the motion sensor obtained...
In this paper we develop a method for estimating static model parameters required for marker-based visual tracking of crane loads. The static model parameters describe both the location of markers, which are used for visual tracking, and the mass center position of the crane load, which is used in the dynamical model for predicting the motion of the crane load. The proposed method is based on a particle...
This paper addresses distributed average tracking for a group of heterogeneous physical agents consisting of single-integrator, double-integrator and Euler-Lagrange dynamics. Here, the goal is that each agent uses local information and local interaction to calculate the average of individual time-varying reference inputs, one per agent. Two nonsmooth algorithms are proposed to achieve the distributed...
Camera tracking is an important issue in many computer vision and robotics applications, such as, augmented reality and Simultaneous Localization And Mapping (SLAM). In this paper, a feature-based technique for monocular camera tracking is proposed. The proposed approach is based on tracking a set of sparse features, which are successively tracked in a stream of video frames. In the developed system,...
The problem of joint parameters and time delay estimation or their tracking by processing of input-output observations arises, when LTI dynamical system has an unknown time delay. It is known that a mean-square error function is multiextremal for time delay even if the system parameters are known in advance. For this purpose an approach used to transform the multiextremal criterion into an unimodal...
The present publication describes a localization concept to determine the 3D Position of passive UHF-RFID transponders. The importance of accurate location information significantly increases with Industry 4.0 in mind. Various applications in production and logistics require the exact location for monitoring the processes and thereby increasing the quality and reliability. The presented system consists...
Nowadays, one of the most interesting and active research topic in computer vision is the analysis of crowd behavior. Crowd is a set of individuals gathered in a particular physical area. Analyzing crowd behavior involves many ways viz., crowd density estimation, crowd motion detection, crowd tracking and crowd behavior recognition. We provide a brief literature survey on crowd behavior analysis from...
Redirected walking allows users to explore a large virtual environment while there is a limitation of the room size. Previous works tried to present users straight path in a virtual environment while they walked on a curved path in reality. We expand a previous technique to present users a various curved path in a virtual environment while they walked on a particular curved path or a straight path...
Body orientation gives useful information on assessing a human's state and/or predicting his/her future actions. This paper presents a method of reliably estimating human body orientation using a LIDAR on a mobile robot by integrating shape and motion information. A shape database is constructed by collecting body section shape data from various viewpoints. The result of matching between an input...
In this research study, we model the interdependency of actions performed by people in a group in order to identify their activity. Unlike single human activity recognition, in interacting groups the local movement activity is usually influenced by the other persons in the group. We propose a model to describe the discriminative characteristics of group activity by considering the relations between...
In this paper, we propose a new characteristic measure relative people density and motion dynamics for the purpose of long-term crowd monitoring. While many related works focus on direct people counting and absolute density estimation, we will show that relative densities provide reliable information on crowd behaviour. Furthermore, we will discuss the derivation of a so-called Congestion Level of...
Understanding where people attention focuses is a challenging and extremely valuable task that can be solved using computer vision technologies. In this paper we address this problem on surveillance-like scenarios, where head and body imagery are usually low resolution. We propose a method to profile the attention of people moving in a known space. We exploit coarse gaze estimation and a novel model...
With the popularization of driving-assistance and self-driving systems, the mutual interference will become a big challenge for automotive radars, which demands the introduction of spectrum sharing technology. Based on the radar ranging using OFDM signals and target tracking, the overall performance of ranging accuracy is considered to be the criterion of spectrum allocation. Aiming to optimally allocate...
We present an improved method for the remote estimation of heart rate from face videos. By relying on visual techniques used for the decomposition of spatial information, we propose a novel pipeline to properly extract and process the time signal containing the heart rate information. In order to validate our approach, a dataset of videos containing subjects in a stationary position has been recorded,...
This paper presents a Nonlinear Model Predictive Control (NMPC) approach for critical maneuvering of unmanned surface vessels (USV) in near-collision situation. The algorithm is formulated as a nonlinear optimization problem that minimize the vessel states' deviation from the time varying reference with collision avoidance as a time varying constraint. The International Regulations for Preventing...
Estimating automatically the degree of language skill by analyzing the eye movements is a promising way to help people from all over the world to learn a new language. In this study, we focus on the English skills of non-native speakers. Our aim is to provide an algorithm that can assess accurately and automatically the TOEIC score after reading English texts for few minutes. As a first step towards...
In this paper, a method that directly estimates motion parameters of a range image sensor using range images and optical flow of color images is proposed. Linear equations for motion parameters are introduced by utilizing optical flow. A three-dimensional (3D) map is constructed by registration of range images between frames using the estimated motion parameters. Experiments to construct a 3D map...
Understanding activities of people in a monitored environment is a topic of active research, motivated by applications requiring context-awareness. Inferring future agent motion is useful not only for improving tracking accuracy, but also for planning in an interactive motion task. Despite rapid advances in the area of activity forecasting, many state-of-the-art methods are still cumbersome for use...
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