Development of a systematic computer vision-based method to analyse and compare images of false identity documents for forensic intelligence purposes-Part I: Acquisition, calibration and validation issues
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Finding relations between image semantics and image characteristics is a problem of long standing in computer vision and related fields. Despite persistent efforts and significant advances in the field, today’s computers are still strikingly unable to achi ...
Digital images, taken for example with a smartphone, are usually geo-tagged with location and viewing direction information. This information is not always accurate due to, for example, GPS inaccuracies in large cities. The aim of this project is to develo ...
We suggest a continuous-domain stochastic modeling of images that is invariant to spatial resolution. Specifically, we are proposing an estimator that is calibrated with respect to the sampling step, and that can potentially handle aliased data. Motivated ...
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In this paper we consider the problem of clipped-pixel recovery over an entire badly exposed image region, using two correctly exposed images of the scene that may be captured under different conditions. The first reference image is used to recover texture ...
Shadows, due to their prevalence in natural images, are a long studied phenomenon in digital photography and computer vision. Indeed, their presence can be a hindrance for a number of algorithms; accurate detection (and sometimes subsequent removal) of sha ...
We propose a novel approach to synthesizing images that are effective for training object detectors. Starting from a small set of real images, our algorithm estimates the rendering parameters required to synthesize similar images given a coarse 3D model of ...
We suggest a continuous-domain stochastic modeling of images that is invariant to spatial resolution. Specifically, we are proposing an estimator that is calibrated with respect to the sampling step, and that can potentially handle aliased data. Motivated ...
The analysis of collections of visual data, e.g., their classification, modeling and clustering, has become a problem of high importance in a variety of applications. Meanwhile, image data captured in uncontrolled environments by arbitrary users is very li ...
Barents Lessons presents the results of a research project in the remote, yet resource-rich and for this reason geo-strategically crucial Barents Sea region. Starting with the thesis that the ocean is an urbanized territory, master students at laba (Labora ...
The current trend in constructing high-end computing systems consists of parallelizing large numbers of processors. A similar trend is observed in digital imaging where multiple camera inputs are utilized to obtain multiple images of a scene and thus enhan ...