5 research outputs found
Blockchain-Based Electronic Voting System for Elections in Turkey
Traditional elections satisfy neither citizens nor political authorities in
recent years. They are not fully secure since it is easy to attack votes. It
threatens also privacy and transparency of voters. Additionally, it takes too
much time to count the votes. This paper proposes a solution using Blockchain
to eliminate all the disadvantages of conventional elections. Security and data
integrity of votes are absolutely provided theoretically. Voter privacy is
another requirement that is ensured in the system. Lastly, the waiting time for
results decreased significantly in the proposed Blockchain voting system.Comment: 4 pages, 4 figures, IEEE styl
A Survey on Computer Vision based Human Analysis in the COVID-19 Era
The emergence of COVID-19 has had a global and profound impact, not only on
society as a whole, but also on the lives of individuals. Various prevention
measures were introduced around the world to limit the transmission of the
disease, including face masks, mandates for social distancing and regular
disinfection in public spaces, and the use of screening applications. These
developments also triggered the need for novel and improved computer vision
techniques capable of (i) providing support to the prevention measures through
an automated analysis of visual data, on the one hand, and (ii) facilitating
normal operation of existing vision-based services, such as biometric
authentication schemes, on the other. Especially important here, are computer
vision techniques that focus on the analysis of people and faces in visual data
and have been affected the most by the partial occlusions introduced by the
mandates for facial masks. Such computer vision based human analysis techniques
include face and face-mask detection approaches, face recognition techniques,
crowd counting solutions, age and expression estimation procedures, models for
detecting face-hand interactions and many others, and have seen considerable
attention over recent years. The goal of this survey is to provide an
introduction to the problems induced by COVID-19 into such research and to
present a comprehensive review of the work done in the computer vision based
human analysis field. Particular attention is paid to the impact of facial
masks on the performance of various methods and recent solutions to mitigate
this problem. Additionally, a detailed review of existing datasets useful for
the development and evaluation of methods for COVID-19 related applications is
also provided. Finally, to help advance the field further, a discussion on the
main open challenges and future research direction is given.Comment: Submitted to Image and Vision Computing, 44 pages, 7 figure
Face-Dubbing++: Lip-Synchronous, Voice Preserving Translation of Videos
In this paper, we propose a neural end-to-end system for voice preserving,
lip-synchronous translation of videos. The system is designed to combine
multiple component models and produces a video of the original speaker speaking
in the target language that is lip-synchronous with the target speech, yet
maintains emphases in speech, voice characteristics, face video of the original
speaker. The pipeline starts with automatic speech recognition including
emphasis detection, followed by a translation model. The translated text is
then synthesized by a Text-to-Speech model that recreates the original emphases
mapped from the original sentence. The resulting synthetic voice is then mapped
back to the original speakers' voice using a voice conversion model. Finally,
to synchronize the lips of the speaker with the translated audio, a conditional
generative adversarial network-based model generates frames of adapted lip
movements with respect to the input face image as well as the output of the
voice conversion model. In the end, the system combines the generated video
with the converted audio to produce the final output. The result is a video of
a speaker speaking in another language without actually knowing it. To evaluate
our design, we present a user study of the complete system as well as separate
evaluations of the single components. Since there is no available dataset to
evaluate our whole system, we collect a test set and evaluate our system on
this test set. The results indicate that our system is able to generate
convincing videos of the original speaker speaking the target language while
preserving the original speaker's characteristics. The collected dataset will
be shared