1,720,977 research outputs found
MAGI: Multistream aerial segmentation of ground images with small-scale drones
No full textIn recent years, small-scale drones have been used in heterogeneous tasks, such as border control, precision agriculture, and search and rescue. This is mainly due to their small size that allows for easy deployment, their low cost, and their increasing computing capability. The latter aspect allows for researchers and industries to develop complex machine-and deep-learning algorithms for several challenging tasks, such as object classification, object detection, and segmentation. Focusing on segmentation, this paper proposes a novel deep-learning model for semantic segmentation. The model follows a fully convolutional multistream approach to perform segmentation on different image scales. Several streams perform convolutions by exploiting kernels of different sizes, making segmentation tasks robust to flight altitude changes. Extensive experiments were performed on the UAV Mosaicking and Change Detection (UMCD) dataset, highlighting the effectiveness of the proposed method
Design of a 3D platform for immersive neurocognitive rehabilitation
No full textIn recent years, advancements in human-computer interaction (HCI) have enabled the development of versatile immersive devices, including Head-Mounted Displays (HMDs). These devices are usually used for entertainment activities as video-gaming or augmented/virtual reality applications for tourist or learning purposes. Actually, HMDs, together with the design of ad-hoc exercises, can also be used to support rehabilitation tasks, including neurocognitive rehabilitation due to strokes, traumatic brain injuries, or brain surgeries. In this paper, a tool for immersive neurocognitive rehabilitation is presented. The tool allows therapists to create and set 3D rooms to simulate home environments in which patients can perform tasks of their everyday life (e.g., find a key, set a table, do numerical exercises). The tool allows therapists to implement the different exercises on the basis of a random mechanism by which different parameters (e.g., objects position, task complexity) can change over time, thus stimulating the problem-solving skills of patients. The latter aspect plays a key role in neurocognitive rehabilitation. Experiments obtained on 35 real patients and comparative evaluations, conducted by five therapists, of the proposed tool with respect to the traditional neurocognitive rehabilitation methods highlight remarkable results in terms of motivation, acceptance, and usability as well as recovery of lost skills
Homography vs similarity transformation in aerial mosaicking: which is the best at different altitudes?
No full textAerial image mosaicking of an area of interest is the process of combining multiple images, of an area with overlapping regions, into a single comprehensive view. In this process, image registration, i.e., the operation of geometric transformation to align and overlay two or more images of the same scene taken from different viewpoints, starting from their common parts, plays a key role in terms of artifacts reduction. In the current state-of-the-art, image registration of aerial images is usually performed through the use of the homography transformation. This occurs because these images are frequently acquired at high altitudes (more than 100 meters) and the homography has always provided excellent performance. The recent widespread of Unmanned Aerial Vehicles (UAVs) has enabled the development of several applications where mosaics are used as reference images for high precision tasks, including Detection, Recognition, and Identification (hereinafter DRI) of people and objects. These tasks need to acquire images at very low altitudes (below 50 meters), in which the homography tends to introduce artifacts during the registration process. Therefore, a different transformation able to limit how an image can be morphed, i.e., the similarity transformation, is necessary to perform the image registration, thus improving the overall accuracy of the obtained mosaics. In this paper, for the first time in literature, a comparison between the homography and similarity transformations is performed. In particular, the comparison is carried out by using three recently released public datasets, i.e., NPU Drone-Map, senseFly, and UAV Mosaicking and Change Detection (UMCD), containing challenging aerial video sequences acquired at high and low altitudes. The experimental tests have pointed out the direct relationship among best image transformation, UAV altitude, and spatial resolution, required to accomplish the DRI tasks reported above
Automatic deception detection in RGB videos using facial action units
No full textThe outcome of situations such as police interrogatory or court trials is strongly influenced by the behaviour of the interviewed subject. In particular, a deceptive behaviour may completely overturn such sensible situations. Moreover, if some specific devices such as polygraph or magnetic resonance are used, the subject is aware of being monitored and thus he may change his behaviour accordingly. To overcome this problem, in this paper a method for detecting deception in RGB videos is presented. The method automatically extracts facial Action Units (AU) from video frames containing the interviewed subject, and classifies them through an SVM as truthful or deception. Experiments on real trial court data and comparisons with the current state of the art show the effectiveness of the proposed method
A Data Compression Module for the SUNSET Platform
Full text linkIn the last two decades, visual data acquisition in underwater environments has dramatically increased due to the need to face a wide range of challenges that still require further research, including site monitoring, seabed anomaly detection, object detection and classification, and many others. Most of these activities require frequent data acquisition and processing over time, even at different altitudes, view angles, and perspectives. Recent improvements of small-scale Autonomous Underwater Vehicles (AUVs), in terms of navigation time, automatic control, and onboard processing, are making these submersible vehicles particularly suitable for activities as those reported above. Moreover, thanks to their cableless navigation, limited size, and agility, small-scale AUVs (hereinafter simply AUVs) can reach sites otherwise inaccessible with other kinds of underwater vehicles (e.g., medium and large AUVs). The payload capacity of current AUVs allows us to equip them with different vision sensors, including Red Green Blue (RGB) camera and Side Scan Sonar (SSS). In this context, an open issue remains the efficient transmission of visual data from AUV through an underwater acoustic network to allow a remote workstation an online and/or real-time data processing. In this paper, a data compression module for the SUNSET platform is presented. The module is composed of a set of novel algorithms that enables compression of RGB and SSS information with and without data loss. The module also implements some novel features, including progressive compression and Region Of Interest (ROI) selection; the first used to gradually transmit the image data (e.g., sites in which the acoustic transmission is a hard task), the second used to transmit, with higher quality than the rest of the image, the items contained in a specific area. Exhaustive experiments on RGB and SSS datasets prove the effectiveness of the presented module
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Variations on the Author
Full text link“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
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe 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
Full text linkWe 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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