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The idea of “smart sensing” includes a permanent monitoring and evaluation of sensor data related to possible measurement faults. This concept requires a fault detection chain covering all relevant fault types of a specific sensor. Additionally, the fault detection components have to provide a high precision in order to generate a reliable quality indicator. Due to the large spectrum of sensor faults...
The paper proposes a framework for in-home physical exercise monitoring based on a Kinect platform. The analysis goes beyond the state-of-the-art solutions by monitoring more joints and offering more advanced reporting capabilities on the movement such as: the position and trajectory of each joint, the working envelope of each body member, the average velocity, and a measure of the user's fatigue...
Simultaneous acquisition of depth and texture information, such as that provided by RGB-D sensors, finds an ever increasing number of applications, including objects modeling, human-machine interfaces, and robot navigation. One of the challenges resulting from the use of densely populated 3D datasets originates from the massive acquisition, management and processing of the data generated. This reality...
The paper investigates a novel approach for building identification in aerial images, that combines a classical segmentation algorithm, the region growing algorithm, a user guided training approach and a supervised learning solution based on support-vector machines. The user is guiding the training procedure by choosing points on the surface of objects of interest, e.g. buildings, as well as points...
Simultaneous acquisition of depth and texture information, such as that provided by RGB-D sensors, finds an ever increasing number of applications, including objects modeling, human-machine interfaces, and robot navigation. One of the challenges resulting from the use of densely populated 3D datasets originates from the massive acquisition, management and processing of the data generated. This reality...
In this paper, an auction-based node selection technique is considered for a risk-aware Robotic Sensor Network (RSN) applied to Critical Infrastructure Protection (CIP). The goal of this risk-aware RSN is to maintain a secure perimeter around the CIP, which is best maintained by detecting high-risk network events and mitigate them through a response involving the most suitable robotic nodes. These...
This paper discusses biology-inspired artificial neural network (NN) solutions able to provide an intelligent connection of the perception to action for the real-time control of androids to be deployed in eldercare home environments.
This paper investigates a novel solution for the recognition of objects of interest in aerial images. The solution builds on a combination of algorithms inspired from the human visual system with classical and modern algorithms. The goal is to achieve intelligent and powerful approaches that allow for fast and automatic treatment of complex images. The methodology that is proposed innovatively combines...
The research community is experiencing nowadays a significant growth in the amount of sensor data made available to several practical applications, particularly those dealing with visual information. The availability of large datasets poses critical challenges for the selection of only relevant features to allow their timely use and interpretation. The recent years marked an increasing interest in...
The automated servicing of vehicles is becoming more and more a reality in today's world. While certain operations, such as car washing, require only a rough model of the surface of a vehicle, other operations, such as changing of a wheel or filling the gas tank, require correct localization of the different parts of the vehicle on which operations are to be performed. The paper describes an image-based...
This paper discusses the design and implementation of a framework that automatically extracts and monitors the shape deformations of soft objects from a video sequence and maps them with force measurements with the goal of providing the necessary information to the controller of a robotic hand to ensure safe model-based deformable object manipulation. Measurements corresponding to the interaction...
The continuous rise in the amount of vehicles in circulation brings an increasing need for automatically and efficiently recognizing vehicle categories for multiple applications such as optimizing available parking spaces, balancing ferry load, planning infrastructure and managing traffic, or servicing vehicles. This paper describes the design and implementation of a vehicle classification system...
The paper addresses the topic of intelligent sensing and mapping of deformable objects' properties for virtualized reality applications. Shape information in form of contours of soft deformable objects tracked over a sequence of images is correlated to the interaction measurements collected at the level of the fingers of a robotic hand by means of neural networks. The proposed solution allows the...
The paper discusses a novel unsupervised learning approach for tracking deformable objects manipulated by a robotic hand in a series of images collected by a video camera. The object of interest is automatically segmented from the initial frame in the sequence. The segmentation is treated as clustering based on color information and spatial features and an unsupervised network is employed to cluster...
This paper employs a neural gas network to obtain a compressed model of 3D geometry of objects, which accounts for elastic behavior as well. Based on the output of the network, we are able to cluster the object into areas of similar geometry and elasticity and then represent the elastic behavior of each cluster by an Elman neural network that models force-displacement behavior without explicit computation...
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