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A complex activity is a temporal composition of sub-events, and a sub-event typically consists of several low level micro-actions, such as body movement of different actors. Extracting these micro actions explicitly is beneficial for complex activity recognition due to actor selectivity, higher discriminative power, and motion clutter suppression. Moreover, considering both static and motion features...
This paper deals with automatic estimation of the horizon in videos from fixed surveillance cameras. The proposed algorithm is fully automatic in the sense that no user input is needed per-camera and it works with various scenes (indoor, outdoor, traffic, pedestrian, livestock, etc.). The algorithm detects moving objects, tracks them in time, assesses some of their geometric properties related to...
Human action recognition is the process of labeling image sequences with action labels. Robust solutions to this problem have applications in domains such as medical care, human-computer interaction and virtual training. The task is challenging for feature extraction due to variations in motion performance, recording settings and inter-personal differences. To meet these challenges, we propose two...
Given a database of spatial trajectories reporting the movement of a set of objects in a time frame, the problem is to discover the groups of objects that stay in close proximity within a geographical area for a significant time. To deal with the problem, techniques for the discovery of collective patterns, e.g. the meeting pattern, have been proposed. Such techniques, however, impose stringent constraints...
Transit advertising provides frequent exposure to a large number of residents in different urban regions. However, traditional methods are generally manual and qualitatively based on a rough estimation, such as the number of passengers taken by a bus or functional regions covered. How to accurately put an advertisement on appropriate transportations becomes an important task for potential business...
Tactical military communication networks operate in highly complex environments. The survivability and the range of these networks, especially the mobile wireless segments, are and will be a challenge for the present and future defence forces. OPAL, an autonomous system, has been previously presented where it extended the range and improved the survivability of tactical military networks using unmanned...
Obstacle detection and tracking is a fundamental task for several Advanced Driver Assistance Systems (ADAS) and self-driving cars. Several approaches have been presented in the literature in the last years and many of them are based on visual sensors. In this paper we propose an approach that uses only stereo cameras to detect and track obstacles and compute visual odometry to get the vehicle's ego-velocity...
Food is important to human for supporting our daily lives. Researchers can perceive food properties through investigation of mastication process. The investigation of in-vivo mastication can be time consuming and inefficient as a panel of volunteers is required. Robotic devices can assist as a platform to carry in-vitro simulation of mastication. This paper proposes a plan of developing a masticatory...
In order to control the interaction of industrial robots with soft materials many computationally-intensive sub-tasks have to be performed in parallel, such as material simulations, control policy optimization or path planning among many others. Since the robot control cannot process the amount of information needed for those tasks, the whole system needs to be split up in two parts: the physical...
We describe and evaluate a novel optimization-based off-line path planning algorithm for mobile robots based on the Counterexample-Guided Inductive Optimization (CEGIO) technique. CEGIO iteratively employs counterexamples generated from Boolean Satisfiability (SAT) and Satisfiability Modulo Theories (SMT) solvers, in order to guide the optimization process and to ensure global optimization. This paper...
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...
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