1,720,959 research outputs found
Garment-based motion capture (GaMoCap): high-density capture of human shape in motion
No full textThis paper presents a new motion capture (MoCap) system, the garment-based motion capture system-GaMoCap. The key feature is the use of an easily wearable garment printed with colour-coded pattern and a generic multicamera setup with standard video cameras. The coded pattern allows a high-density distribution of markers per unit of surface (about 40 markers per 100 cm), avoiding markers-swap errors. The high density of markers reconstructed makes possible a simultaneous reconstruction of shape and motion, which gives several concurrent advantages with respect to the state of the art and providing performances comparable with previous marker-based systems. In particular, we provide effective solutions to counter the soft-tissue artefact which is a common problem for garment-based techniques. This effect is reduced using Point Cluster Technique to filter out the points strongly affected by non-rigid motion. Uncertainty of motion estimation has been experimentally quantified by comparing with a state-of-the-art commercial system and numerically predicted by means of a Monte Carlo Method procedure. The experimental evaluation was performed on three different articulated motions: shoulder, knee and hip flexion-extension. The results shows that for the three motion angles estimated with GaMoCap, the system provides comparable accuracies against a commercial VICON system
Development and Characterization of a Safety System for Robotic Cells Based on Multiple Time of Flight (TOF) Cameras and Point Cloud Analysis
No full textIn this paper, a vision system for safety applications in human-robot collaboration is presented. The system is based on two Time-Of-Flight (TOF) cameras for 3D acquisition. The point clouds are registered in a common reference system, and human and robot recognition are then implemented. Human recognition is performed using a customized version of the Histogram of Oriented Gradient (HOG) algorithm. Robot recognition is achieved using a procedure based on the Kanade-Lucas-Tomasi (KLT) algorithm. Two safety strategies have been developed. The first one is based on the definition of suitable comfort zones of both the operator and the robot; the second implements virtual barriers between the operator and the robot. The vision system has been characterized in terms of (i) human and robot recognition performance, (ii) correctness of the detection of safety situations and (iii) evaluation of the time delays in the detection. The results show that the human operator is robustly recognized provided that he moves frontally with respect to the TOF cameras and the robot is always recognized. The safety situations are always identified correctly with an average time delay of 0.86 0.63 s (k=1)
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Assessment of mental stress through the analysis of physiological signals acquired from wearable devices
No full textMental stress is a physiological state that directly correlates to the quality of life of individuals. Generally speaking, but especially true for disabled or elderly subjects, the assessment of such condition represents a very strong indicator correlated to the difficulties, and, in some case, to the frustration that derives from the execution of a task that results troublesome to be accomplished. This article describes a novel procedure for the assessment of the mental stress level through the use of low invasive wireless wearable devices. The information contained in electrocardiogram, respiratory signal, blood volume pulse, and electroencephalogram was extracted to set up an estimator for the cognitive workload level. A random forest classifier was implemented to assess the level of mental stress starting from a pool of 3481 features computed from the aforementioned physiological quantities. The proposed system was applied in a scenario in which two different mental states were elicited in the subject under investigation: first, a baseline resting condition was induced by the presentation of a relaxing video; then a stressful cognitive state was provoked by the administration of a mental arithmetic task. The random forest classifier shows an accuracy of 97.5% in discerning between these two mental states
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Data fusion of images and 3D range data
No full textA robot is a machine that embodies decades of research and development. Born as a simple mechanical devices, these machines evolved together with our technology and knowledge, reaching levels of automation never imagined before. The modern dream is represented by the cooperative robotics, where the robots do not just work for the people, but together with the people. Such result can be achieved only if these machines are able to acquire knowledge through perception, in other words they need to collect sensor measurements from which they extract meaningful information of the environment in order to adapt their behavior. This thesis speaks about the topic of the autonomous object recognition and picking for Automated Guided Vehicles, AGVs, robots employed nowadays in the automatic logistic plants. The development of a technology capable of achieving such task would be a significant technological improvement compared to the structure currently used in this field: rigid, strongly constrained and with a very limited human machine interaction. Automating the process of picking by making such vehicles more smart would open to many possibilities, both in terms of organization of the plants, both for the remarkable economic implications deriving from the abatement of many of the associated fixed costs. The logistics field is indeed a niche, in which the costs of the technology represent the true limit to its spread, costs due mainly to the limitations of the current technology. The work is therefore aimed at creating a stand-alone technology, usable directly on board of the modern AGVs, with minimal modifications in terms of hardware and software.
The elements that made possible such development are the multi-sensor approach and data-fusion. The thesis starts with the analysis of the state of the art related of the field of the automated logistic, focusing mostly on the most innovative applications and researches on the automatization of the load/unload of the goods in the modern logistic plants. What emerges form the analysis it is that there is a technological gap between the world of the research and the industrial reality: the results and solutions proposed by the first seem not match the requirements and specification of the second.
The second part of the thesis is dedicated to the sensors used: industrial cameras, planar 2D safety laser scanners and 3D time of flight cameras (TOF). For every device a specific (and independent) process is developed in order to recognize and localize Euro pallets: the information that AGVs require in order to perform the picking of an object are the three coordinates that define its pose in the 2D space, , position and attitude. The focus is addressed both on the maximization of the reliability of the algorithms and both on the capability in providing a correct estimation of uncertainty of the results. The information content that comes from the uncertainty represents a key aspect for this work, in which the probabilistic characterization of the results and the adoption of the guidelines of the measurement field are the basis for a new approach to the problem. That allowed both the modification of state of the art algorithms both the development of new ones, developing a system that in the final implementation and tests has shown a reliability in the identification process sufficiently high to fulfill the industrial standards, 99\% of positive identifications.
The third part is devoted to the calibration of system. In order to ensure a reliable process of identification and picking it is indeed fundamental to evaluate the relations between the sensing devices, sensor-sensor calibration, but also to relate the results obtained with the machine, sensor-robot calibration. These calibrations are critical steps that characterize the measurement chain between the target object and the robot controller. From that chain depends the overall accuracy in performing the forking procedure and, more important, the safety of such operation.
The fourth part represents the core element of the thesis, the fusion of the identifications obtained from the different sensors. The multi-sensor approach is a strategy that allows the overcome of possible operational limits due to the measurement capabilities of the individual sensors, taking the best from the different devices and thus improving the performance of the entire system. This is particularly true in the case in which there are independent information sources, these, once fused, provide results way more reliable than the simple comparison of the data. Because of the different typology of the sensors involved, Cartesian ones like the laser and the TOF, and perspective ones like the camera, a specific fusion strategy is developed. The main benefit that the fusion provides is a reliable rejection of the possible false positives, which could cause very dangerous situations like the impact with objects or worst. A further contribution of this thesis is the risk prediction for the maneuver of picking. Knowing the uncertainty in the identification process, in calibration and in the motion of the vehicle it is possible to evaluate the confidence interval associated to a safe forking, the one that occurs without impact between the tines and the pallet. That is critical for the decision making logic of the AGV in order to ensure a safe functionality of the machine during all daily operations.
Last part of the thesis presents the experimental results. The aforementioned topics have been implemented on a real robot, testing the behavior of the developed algorithms in various operative conditions
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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