1,720,985 research outputs found
Spatial-Temporal Analysis of In-Air Hand Gesture Signature Recognition
No full textA traditional online handwritten signature recognition system requires direct contact with the acquisition device that may leave a trace on the device's surface. This results in a signature being easily tracked and imitated. Such an acquisition device is not commonly available, while the public usually shares this device. Germs could be accumulated on the devices, and thus, a hygiene concern has risen. A novel approach in recognising a signature based on hand motion is proposed to address these issues, namely in-air hand gesture signature (iHGS). A low-cost acquisition device – the Microsoft Kinect sensor, is used to capture hand gesture-based signatures. Unlike the conventional dynamic signature, the captured hand gesture-based signature is a sequence of images containing the signing action's spatial and temporal information. To detect and extract the region of interest, a hand region is first located and segmented from a depth image by a predictive hand segmentation algorithm. The resultant volume data is then condensed and transformed into three directional plane projections. Specifically, XY plane projection employs Motion History Image (MHI) to obtain a compact motion representation image, whist XT plane projection (X-profile) and YT plane projection (Y-profile) project the volume data along the x-axis and y-axis, respectively. Vector-based and image-based features are extracted from the transformed image templates. A vector-based feature is a one-dimensional vector produced through the image templates into a vector space that numerically quantifies the local information of an image. An image-based feature is a visual representation feature that combines one or more image templates into a static image that better visualizes a hand gesture signature's spatial and temporal information. In the experimental analysis, classification performance and system robustness are systematically assessed using a self-collected dataset, the iHGS dataset. For the classification analysis, the k-NN and SVM classifiers are employed to classify the vector-based features. A pre-trained deep learning model is used to classify imagebased features. On the other hand, system robustness is also investigated against two common forgery attacks, (1) random forgeries and (2) skilled forgeries. Additionally, performance comparisons are conducted between the proposed methods with several state-of-art approaches. The overall performance analysis has demonstrated the potential and efficiency of the proposed methods in recognising and verifying in-air hand gesture signature recognition
Dynamic Signature Verification Based On Hybrid Discrete Wavelet-Fourier Transform And Fusion Approaches
No full textThe research in this thesis is to investigate and implement a biometric verification system incorporates with feature extraction process which extracted a discriminative yet compact feature from a dynamic signature. The purpose is to obtain a reliable method that can classify between genuine and forgery classes of a signature data
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
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
In-air hand gesture signature recognition system based on 3-dimensional imagery
No full textA traditional online handwritten signature recognition system requires direct contact to acquisition device and usually will leave a traceable print on the surface. This made a signature possible and vulnerable to certain attempts of tracking and imitated. Looking into this shortfall, this paper proposes a novel approach to recognise an individual based on his/ her in-air hand motion while signing his/her signature. In this study, a low-cost acquisition device – Microsoft Kinect sensor is adopted to capture an image sequence of hand gesture signature. Palm region is first located and segmented through a predictive palm segmentation algorithm, which are then combined to generate a volume data. The volume data is condensed and reduced into a motion representation image by means of Motion History Image (MHI), which produces rich motion and temporal information. Several features are extracted from the MHI for empirical evaluation. Two classical recognition modes – identification and verification, are testified with an in-house database (HGS database). The proposed system achieves 90.4% identification accuracy and 3.22% equal error rate in verification mode. The experimental results substantiated the potential of the proposed system
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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