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This paper proposes a new approach for analysing crowded video scenes. The proposed approach decomposes the scene motion dynamics into a graph of interconnected atomic elements of coherent motions named Motion Units (MUs). Different MUs cover scene's local regions with different size and shape, which can even overlap. MUs relationships are analysed to discover the scene entrances and exits. Dominant...
Multi-object video segmentation and multi-object tracking are very similar in the aspect that both determine the locations and maintain the identities of the objects of interest (targets) in each frame of the video. Our approach takes advantage of this fact and uses the strengths of one task to improve the accuracy of the other. In our framework, the multi-object tracking and segmentation modules...
We present a novel and configurable synthetic data generator for evolving region trajectories that emulates certain characteristics of a given input dataset, such as the spatial position, velocity, lifespan, and geometry shape and size. This tool aims to facilitate faster prototyping and evaluation of new spatiotemporal data mining algorithms that operate on a specific type of trajectory data, of...
In this paper, a redundantly actuated chewing robot with two higher kinematic pairs (HKPs) is presented, which can be used in performance test and evaluation of denture material. The robot has six actuators, but only has four degrees of freedom, due to constraints of two HKPs which mimic two temporomandibular joints (TMJs) of human. Quasi-static force analysis in occlusion status is performed to calculate...
We demonstrate the application of predictive functional control to a real-life position-control problem of a mechatronic system using a state observer-based internal model (PFC-OBIM). In the literature, the control method has been shown to be effective in simulation. However, no experimental validation has been conducted so far. Hence, we conduct a few experimental tests using a single-axis table...
Kalman Filters are utilised for filtering and estimation in a large set of application. Here, this methodology is utilised for trajectory estimation of an underwater robot. In this work, three Kalman Filter methods are proposed for trajectory estimation. There are: Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF) and Central Difference Kalman Filter (CDKF). Simulation results are presented...
This paper discusses about the trajectory planning and controlled maneuvering of the vehicle in parking assist mode. The objective of the proposed algorithm is to use low-cost hardware like ultrasonic sensor in order to provide automated parking assist to the vehicle. The concept of grid occupancy is formulated in free space detection algorithm to compute lateral-longitudinal grid cell vacancy. The...
This paper explores recent achievements and novel challenges of the annoying privacy-preserving big data stream mining problem, which consists in applying mining algorithms to big data streams while ensuring the privacy of data. Recently, the emerging big data analytics context has conferred a new light to this exciting research area. This paper follows the so-depicted research trend.
Spatiotemporal event sequences (STESs) are the ordered series of event types whose evolving region-based instances frequently follow each other in time and are located closeby. Previous studies on STES mining require significance and prevalence thresholds for the discovery, which is usually unknown to domain experts. As the quality of the discovered STESs is of great importance to the domain experts...
This paper studies the adaptive position and velocity tracking control for high speed train with asymmetric nonlinear input saturation. Adaptive tracking control for high speed train encounters great challenges when the train dynamics containing nonlinearities, asymmetric input saturation and unknown external disturbances. An adaptive tracking control method is developed by means of sliding mode technique...
In this paper, we propose a work flow for processing and analysing large-scale tracking data with spatio-temporal marks that uses an infrastructure for machine learning methods based on a meta-data representation of point patterns. The tracking log (IP address) of cyber security devices usually maps to geolocation and timestamp, such data is called spatiotemporal data. Existing spatio-temporal analysis...
Due to the sparse distribution of road video surveillance cameras, precise trajectory tracking for hit-and-run vehicles remains a challenging task. Previous research on vehicle trajectory recovery mostly focuses on recovering trajectory with low-sampling-rate GPS coordinates by retrieving road traffic flow patterns from collected GPS information. However, to the best of our knowledge, none of them...
This paper presents an approach to trajectory tracking control for autonomous vehicles subject to parametric uncertainties. Such uncertainties may have the potential to significantly decrease the performance of the system, even to the point of destabilizing it. Therefore, these parametric variations must be taken into account during the design of the controller. To solve the trajectory tracking problem...
In the past years Unmanned Aerial Vehicles (UAVs) have received considerable attention from the scientific community. The trajectory control is a fundamental block that a flight control system must properly address. However, a recent approach based on fractional calculus has shed a new light into this area, allowing the well tested PID controller to be improved even further. One advantage is that...
This paper presents an external hybrid force/pose controller for a robotic manipulator using a cascade scheme with two control loops. In the outer loop there is a force controller that acts as a perturbation for the position reference, whose purpose is to regulate the force applied by the end-effector during the interaction; the inner loop, which is used to control the end-effector pose (i.e., position...
ORB-SLAM2 is one of the better-known open source SLAM implementations available. However, the dependence of visual features causes it to fail in featureless environments. With the present work, we propose a new technique to improve visual odometry results given by ORB-SLAM2 using a tightly Sensor Fusion approach to integrate camera and odometer data. In this work, we use odometer readings to improve...
Lane estimation plays a central role for Driver Assistance Systems, therefore many approaches have been proposed to measure its performance. However, no commonly agreed metric exists. In this work, we first present a detailed survey of the current measures. Most of them apply pixel-level benchmarks on camera images and require a time-consuming and fault-prone labeling process. Moreover, these metrics...
This paper focuses on target motion analysis by fusion of information from two moving acoustic sensors. These two sensors may obtain small measurements in order to make quick analysis of moving targets. In this situation, conventional approaches often fail to find accurate motion of targets. In this paper, a fusion algorithm for target motion analysis designed to handle this situation is proposed...
Most of the available robot programming by demonstration (PbD) approaches focus on learning a single task, in a given environmental situation. In this paper, we propose to learn multiple tasks together, within a common environment, using one of the available PbD approaches. Task-parameterized Gaussian mixture model (TP-GMM) is used at the core of the proposed approach. A database of TP-GMMs will be...
The focus of the computing industry continues to shift towards designing and building intelligent systems that can handle and learn from large amounts of data. The availability of powerful processing hardware like GPUs and TPUs, has powered the tremendous success of many sophisticated resource intensive machine learning algorithms. However as device scaling and energy dissipation fast approach the...
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