1,721,181 research outputs found
TIFS: A hybrid scheme integrating partitioned iterated function system and linear transforms
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An enterprise rights management system for on-the-field maintenance facilities
No full textOn-the-field maintenance of complex equipments, that may involve multiple subjects and stakeholders, is one of most challenging scenarios for Enterprise Rights Management (ERM). In this paper, we present an ERM system that guarantees the 'on-site' protection of information confidentiality. In particular, our system features local data encryption and minimal data transfers. A secure key management protocol is executed by the devices operating on-site and the remote manufacturer's support center and guarantees an efficient and dynamic enforcement of arbitrary data-provider-defined access policies. Operator identities are verified by means of strong multi-biometric verification schemes whilst protecting their biometries by means of cancelable biometries. To this end, we provide the first experimental evaluation of cancelable biometrics based on the fusion of face and voice biometries, that may be of independent interest
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
Improving face recognition in low quality video sequences: Single frame vs multi-frame super-resolution
No full textRe-Identification aims to detect the presence of a subject spotted in one video in other videos. Traditional methods use information extracted from single frames like color, clothes, etc. A sequence in time domain of consecutive subject images could contain a greater amount of information compared with a single image of the same subject. Typically, these sequences are taken from surveillance cameras at very poor resolution. Even with modern cameras the resolution can be a problem when dealing with a subject who is far from the camera. A possible way of handling low resolution images is by using a multi-frame super-resolution algorithm. Multi-frame super-resolution image reconstruction aims at obtaining a high-resolution image by fusing a set of low-resolution images. Low-resolution images are usually subject to some degradation which causes substantial information loss. Therefore, contiguous images in a sequence could be viewed as a degraded version (SR image) of an image at higher resolution (HR image). Using a multi-frame SR algorithm could achieve a restoration of the HR image. This work aims to investigate the possibility of using a multi-frame super-resolution algorithm to enhance the performance of a classic re-identification system by exploiting information provided by video sequences made available by a video surveillance system. In the case that the SR technique employed results in an effective performance enhancement, we intend to show empirically how many match frames are required to have an effective improvement
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