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Kernel-based machine learning methods are gaining increasing interest in flow modeling and prediction in recent years. Gaussian process (GP) is one example of such kernel-based methods, which can provide very good performance for nonlinear problems. In this work, we apply GP regression to flow modeling and prediction of athletes in ski races, but the proposed framework can be generally applied to...
Physical rehabilitation training using an intelligent control system is important for the people with lower limb dysfunction. In this paper, the sit-to-stand (STS) trajectory of health persons is researched based on STS biomechanics model. Several novel mechanical structures for intelligent lower limb STS rehabilitation training system are presented. According to the mechanical analysis of its finite...
The online writer identification is a required component in many applications of Computer vision and Pattern Recognition. The offline writer identification is more developed in literature due to the use of traditional system based on Image Processing. There is a lack of works done in the case of online writer identification. In this paper, we propose a novel method to text independent writer identification...
One of the complicated issue in compliance control for rehabilitation and assistive robots is to predict right human's motion intention. In this paper, we have proposed an algorithm to estimate Desired Motion Intention (DMI) so that better compliance could be provided by the rehabilitation and assitive robots. Proposed algorithms is based on Extreme Learning Machine (ELM) and takes inputs from different...
The agricultural production video record is an important primitive data in the establishment of agricultural product quality traceability system and digital monitoring system. This paper presents the feature extraction and automatic recognition system of the typical production activities in the agricultural production video record based on the machine learning theory. The system consists of the feature...
Due to the diversity of body movements and uncertainty of recording occasion, human action recognition is still a challenging task, especially in real world. This paper provides a new method of representing the video with mid-level vision representation which is extracted from the discriminative supervoxels. In the proposed method, the discriminative supervoxels we extracted through a learning phase...
Object detection from still images has been among the most active and challenging area in computer vision recently. In contrast, fully supervised object detection from video has rarely been investigated. In this paper, we propose an algorithm to improve the performance of object detection from video. Our proposed method is based on an empirical property that the trajectory of an object is important...
Motion trajectory tracing in indoor environment has become increasingly important, has the potential to support a broad array of applications including elder care, business analysis, pedestrian navigation. Traditional approaches involve wearable sensors, specialized hardware installations. This paper presents SmartMTra, an infrastructure-free, inertial sensor based motion trajectory tracing system...
In this study, human activity identification is approached as a record, analyze and model from the video sequence as you observe the scene in time methodology. The computational approach has two stages: training and identification. During the training stage, specific human activities are identified and characterised by employing modelling of medium-term movement flow through streaklines. Each streak-lines...
This paper presents a novel method for learning a pose lexicon comprising semantic poses defined by textual instructions and their associated visual poses defined by visual features. The proposed method simultaneously takes two input streams, semantic poses and visual pose candidates, and statistically learns a mapping between them to construct the lexicon. With the learned lexicon, action recognition...
Currently, minimally invasive surgery (MIS) is applied in the diagnosis and surgery using an endoscope or a catheter for neurosurgery and for endovascular diseases, such as aneurysm, atrial septal defect (ASD), embolization, and cerebral aneurysm. This study proposes virtual-reality (VR) simulator system for double interventional cardiac catheterization (ICC) using fractional order vascular access...
This article is focused on possibilities of an implementation of information technologies in a learning of self-defense. The self-defense is a field which is more and more necessary in our life. During our research, we tried to find out if it is possible to connect information technologies with learning of self-defense for more effective results. We used VICON system for visualization of body motion...
Resistance training of the leg extensor muscles is an important intervention in rehabilitation and prevention of musculoskeletal disorders such as hip or knee arthrosis and osteoporosis. With current training equipment, neither the exercise trajectory can be optimized nor the loadings on structures of the musculoskeletal system can be controlled. To overcome these limitations an experimental research...
The goal of this paper is to contribute to the understanding of the dynamics of recurrent neural networks. Specifically, we establish conditions for the existence of stable limit cycles, whose existence is equivalent to the echo state property. We provide sufficient conditions for the convergence to a trajectory that is uniquely determined by the driving input signal, independently of the initial...
Muscle weakness is one of the major deficits after stroke but specific strength training is seldom included in robot-assisted rehabilitation. At the same time, the emergence of robotic devices for stroke therapy offers technical possibilities for strength training. We propose a control strategy for strength training that is based on a viscous force field shaped towards the patient's performance abilities...
Spoken dialog represents a comfortable way of the human-machine cooperation. Dialogue technology is language-dependent due to its relationship to the natural language processing. For a long time, there did not exist any resources for designing advanced dialogue interaction in the Slovak language. Therefore, the new corpus of human-human dialogues started to be prepared. Suitable dialogue interactions...
Serious games based physical therapy is currently gaining a lot of interest by the physiotherapists and game developers that are using new natural user interfaces devices to assure an easy interaction between the user under rehabilitation and his avatar immersed in a virtual reality scenario. Arm motion training, as part of stroke rehabilitation program, can be one of the main objectives of the serious...
This paper manly presented kicking design motion of humanoid robots using a reinforcement learning method which is based on the Q-learning. First, this method build a multidirectional fixed-point kicking model, which is based on the offset of kicking point, the foot space motion trajectory and ZMP stability criterion, and that makes subsequent train costs much less time. Besides, discretization of...
Due to the urgent need for Minimally Invasive Surgeries (MIS), all kinds of surgical robots have been developed and investigated intensively in last decades, which can both release the fatigues of surgeons and speed up the process of wound healing. Tendon-Driven Serpentine Manipulator (TSM) maybe among the most widely adopted and promising ones to turn robot assisted MIS into reality. But due to the...
Here we explore a visual display technique for low frame rate virtual environments called low persistence (LP). This involves displaying the rendered frame for a single display frame and blanking the screen while waiting for the next frame to be generated. To gain greater knowledge about the LP technique, we have conducted a user study to evaluate user performance and learning during a dynamic target...
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