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Utilization of the digital human has been tried for the human work-related evaluation for industrial products and the prevention of an injury during sports activity. The human modeling for the posture generation of digital human are studied actively. In this study, we aim for the construction of the skeleton model for forearm pro-/supination to be performed in everyday life frequently. The forearm...
Inverse dynamics analysis, which enables the information about joint force/torque of human body from the measured motion data, is a traditional tool in biomechanical studies. Conventionally, measurements of body motion are obtained by motion capture cameras, of which the bulkiness and high cost make it hard to capture some movements that need broad range of space. As an alternative, inertial motion...
A sEMG signal is useful for the control of the wearable robots because its measurement is relative-easy and the joint torque can be estimated from sEMG signals of related multiple muscles. However, estimation methods of sEMG signals are not always available for all users. On the other hand, an EEG signal is one of the biological signals which might be the substitute for a sEMG signal because an EEG...
Distributed estimation of a deterministic scalar parameter by using quantized data in the presence of spoofing attacks, which modify the statistical model of the physical phenomenon, is considered. The paper develops an efficient heuristic approach to jointly detect attacks and estimate under spoofing attacks that are undetectable by a traditional approach that relies on noticing the data is not consistent...
This paper is concerned with pose (position and orientation) estimation of robotic end-effectors under low speed motion where its acceleration is far less than the gravity. An Extended Kalman Filter (EKF) is designed to fuse measurements from an inertial measurement unit (IMU) and a SE(3) measurement system. The IMU consists of a tri-axis accelerometer and a tri-axis gyroscope that sense the end-effector...
In this paper we provide a scheme for estimating the minimum achievable exponential decay rate of a switched linear system via output feedback control. The output feedback stabilization of switched linear systems using path-dependent controllers is characterized exactly in [8] in terms of an increasing family of linear matrix inequalities; the feasibility of any one of these inequalities allows for...
Tracking Human activity at home plays a growing factor in fields of security, and of bio-medicine. Microsoft Kinect is a non-wearable sensor that aggregate depth images with traditional optical video frames to estimate individuals' joints' location for kinematic analysis. When the subject of interest is out of Kinect coverage, or not in line of sight, the joints' estimations are distorted, which reduce...
In this paper we present and investigate a complex control framework based on Nonlinear Model Predictive Control (NMPC) to achieve the unstable equilibria, and Moving Horizon Estimation (MHE) to estimate the actual state and parameters of a Pendubot. This fast, under-actuated nonlinear mechatronic system apparently poses a challenging benchmark problem that might benefit from a nonlinear optimization...
Emerging wireless sensor networks (WSNs) aim to overcome current needs for additional backbone infrastructure in mobile networks. Confronted with enormous requirements in terms of spectrum and energy efficiency, WSNs have been shown to benefit from distributed source coding (DSC) by means of multi-route redundancy. However, DSC in WSNs yields low performance regarding the correlation estimation of...
Joint spectrum sensing and direction of arrival (DOA) estimation is often necessary in communication applications, such as Cognitive Radio (CR). In this paper, we consider joint DOA and carrier frequency recovery of several transmissions as well as signal reconstruction from sub-Nyquist samples to overcome the sampling rate bottleneck of the wideband signals a CR typically deals with. We present two...
Articulated hand pose recovery in egocentric vision is useful for in-air interaction with the wearable devices, such as the Google glasses. Despite the progress obtained with the depth camera, this task is still challenging with ordinary RGB cameras. In this paper we demonstrate the possibility to recover both the articulated hand pose and its distance from the camera with a single RGB camera in egocentric...
We propose a new Gaussian mixture model (GMM)-based probabilistic point set registration method, called Local Structure Preservation (LSP), which is aimed at complex non-rigid and articulated deformations. LSP integrates two complementary shape descriptors to preserve the local structure. The first one is the Local Linear Embedding (LLE)-based topology constraint to retain the local neighborhood relationship,...
We consider the problem of diluting common randomness from correlated observations by separated agents. This problem creates a new framework to study statistical privacy, in which a legitimate party, Alice, has access to a random variable X, whereas an attacker, Bob, has access to a random variable Y dependent on X drawn from a joint distribution pX,Y. Alice's goal is to produce a non-trivial function...
In this paper, a new spectrum sensing framework is proposed for radar communications, which recovers other informative states associated with realistic radar environments, e.g. fading channel gains and unknown noise variance, when detecting the occupancy of primary-band. We firstly formulate a dynamic state-space model by full considering the unknown noise variance and time-variant flat fading channel...
In this paper we present an approach to hand pose estimation that combines both discriminative and modelbased methods to overcome the limitations of each technique in isolation. A Randomised Decision Forests (RDF) is used to provide an initial estimate of the regions of the hand. This initial segmentation provides constraints to which a 3D model is fitted using Rigid Body Dynamics. Model fitting is...
Many studies on action recognition from the third-person viewpoint have shown that articulated human pose can directly describe human motion and is invariant to view change. However, conventional algorithms that estimate articulated human pose cannot handle ego-centric images because they assume the whole figure appears in the image; only a few parts of the body appear in ego-centric images. In this...
This paper proposes a new approach to model arm pose configuration from color images based on the learned features and arm part structure constraints. It aims to model human arm pose without assuming of a particular clothing style, action category and background. It uses an energy model that describes the dependence relationships among arm joints and parts. A joint convolutional neural network (J-CNN)...
Classically robot force control passes through joint torques measurement or estimation. Within this context, classical torque sensing technologies rely on current sensing on motor windings and on torsion sensing on motor shaft. An alternative approach was recently proposed in [1] and combines whole-body distributed 6-axis force/torque (F/T) sensors, gyroscopes, accelerometers and tactile sensors (i...
Intertrack interference (ITI) is one of the most severe impairments in shingled magnetic recording (SMR). The use of Multihead Multitrack (MHMT) detection can best handle this impairment, but increases complexity. Consider a symmetric two-head two-track (2H2T) system given by ra(D)=x-a(D)h(D)+εxb(D)h(D)+na(D) and rb(D)=εxa(D)h(D)+xb(D)h(D)+nb(D), where xa(D), xb(D) and ra(D), r (D) are the input sequences...
In this paper, we present an algorithm for estimating 3D hand skeleton model from a single depth image based on the Active Shape Model framework. We first collect a large amount of training depth images, representing all articulated hand shape variations, and a set of hand joint points are labeled on these depth images. To accommodate the wide variations of hand articulations, we represent the hand...
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