2,225 research outputs found
A Comparative Evaluation of Heart Rate Estimation Methods using Face Videos
This paper presents a comparative evaluation of methods for remote heart rate
estimation using face videos, i.e., given a video sequence of the face as
input, methods to process it to obtain a robust estimation of the subjects
heart rate at each moment. Four alternatives from the literature are tested,
three based in hand crafted approaches and one based on deep learning. The
methods are compared using RGB videos from the COHFACE database. Experiments
show that the learning-based method achieves much better accuracy than the hand
crafted ones. The low error rate achieved by the learning based model makes
possible its application in real scenarios, e.g. in medical or sports
environments.Comment: Accepted in "IEEE International Workshop on Medical Computing
(MediComp) 2020
FaceQnet: Quality Assessment for Face Recognition based on Deep Learning
In this paper we develop a Quality Assessment approach for face recognition
based on deep learning. The method consists of a Convolutional Neural Network,
FaceQnet, that is used to predict the suitability of a specific input image for
face recognition purposes. The training of FaceQnet is done using the VGGFace2
database. We employ the BioLab-ICAO framework for labeling the VGGFace2 images
with quality information related to their ICAO compliance level. The
groundtruth quality labels are obtained using FaceNet to generate comparison
scores. We employ the groundtruth data to fine-tune a ResNet-based CNN, making
it capable of returning a numerical quality measure for each input image.
Finally, we verify if the FaceQnet scores are suitable to predict the expected
performance when employing a specific image for face recognition with a COTS
face recognition system. Several conclusions can be drawn from this work, most
notably: 1) we managed to employ an existing ICAO compliance framework and a
pretrained CNN to automatically label data with quality information, 2) we
trained FaceQnet for quality estimation by fine-tuning a pre-trained face
recognition network (ResNet-50), and 3) we have shown that the predictions from
FaceQnet are highly correlated with the face recognition accuracy of a
state-of-the-art commercial system not used during development. FaceQnet is
publicly available in GitHub.Comment: Preprint version of a paper accepted at ICB 201
A computational model for generating visually pleasing video game maps
In this work we introduce a computational model based on theories of graphical design to generate visually pleasing video game maps. We cast the problem of map generation as an optimization problem and prove it to be computationally hard. Then, we propose a heuristic search approach to solve the map generation problem and use it to generate levels of a clone of Super Mario Bros (SMB) called Infinite Mario Bros (IMB). Before evaluating the levels of IMB generated by our system, we perform a detailed study of the approaches commonly used to evaluate the content generated by computer programs. The evaluation used in previous works often relies on computational metrics. While these metrics are important for an initial exploratory evaluation of the content generated, it is not clear whether they are able to capture the player’s perception of the content generated. In this work we compare the insights gained from a user study with IMB levels generated by different systems with the insights gained from analyzing computational metric values. Our results suggest that current computational metrics should not be used in lieu of user studies for evaluating content generated by computer programs. Using the insights gained in our previous experiment, we performed another user study to evaluate the IMB levels generated by our method. The results show the advantage of our method over other approaches in terms of visual aesthetics and enjoyment. Finally, we performed one last user study that showed that our method is able to generate IMB levels with striking similarity to SMB levels created by professional designers.Neste trabalho apresentamos um modelo computacional baseado em teorias de design para gerar mapas de jogos de plataforma visualmente agradáveis. Nós estudamos o problema de geração de mapas como um problema de otimização e provamos que uma versão simplificada do problema é computacionalmente difícil. Em seguida, propomos uma abordagem de busca heurística para resolver o problema de geração de mapas e utilizamos ela para gerar níveis de um clone do Super Mario Bros (SMB), chamado Infinite Mario Bros (IMB). Antes de avaliar os níveis de IMB gerados pelo nosso sistema, realizamos um estudo detalhado das abordagens comumente utilizadas para avaliar o conteúdo gerado por programas de computador. A avaliação utilizada em trabalhos anteriores utiliza apenas métricas computacionais. Embora esses indicadores são importantes para uma avaliação inicial e exploratória do conteúdo gerado, não é claro se são capazes de capturar a percepção do jogador sobre o conteúdo gerado. Neste trabalho, comparamos os conhecimentos adquiridos a partir de um estudo com seres humanos usando níveis de IMB gerados por diferentes sistemas, com os conhecimentos adquiridos a partir de análise dos valores de métricas computacionais. Os nossos resultados sugerem que as m ́etricas computacionais atuais não devem substituir estudos com seres humanos para avaliar o conteúdo gerado por programas de computador. Usando os conhecimentos adquiridos em nosso experimento anterior, foi realizado outro estudo com seres humanos para avaliar os níveis de IMB gerados pelo nosso método. Os resultados mostram a vantagem do nosso método em relação a outras abordagens em termos de estética visual e diversão. Finalmente, foi realizado outro estudo com seres humanos, mostrando que o nosso método é capaz de gerar níveis de IMB semelhantes aos níveis de SMB criados por designers profissionais.Coordenação de Aperfeiçoamento de Pessoal de Nível Superio
Searching for Uncollected Litter with Computer Vision
This study combines photo metadata and computer vision to quantify where
uncollected litter is present. Images from the Trash Annotations in Context
(TACO) dataset were used to teach an algorithm to detect 10 categories of
garbage. Although it worked well with smartphone photos, it struggled when
trying to process images from vehicle mounted cameras. However, increasing the
variety of perspectives and backgrounds in the dataset will help it improve in
unfamiliar situations. These data are plotted onto a map which, as accuracy
improves, could be used for measuring waste management strategies and
quantifying trends.Comment: 17 pages, 6 figure
Spectrum sharing in cognitive radio networks
Cognitive radio networks are the next step to tackle scarcity in wireless networks given the increasing demand of radioelectric spectrum where the proposed solution is to share said resource to improve this situation. In the present article, a review of the current state of spectrum sharing in cognitive radio networks. To achieve this purpose, the articles published over the last 4 years on the matter were reviewed including topics such as mobile networks and TV. Some studies and simulations proposed to share the spectrum is shown. The current state of the studies reveals that there has been significant progress in this research area yet it is necessary to continue similar studies and set in motion different schemes
Adoption and diffusion of double entry book-keeping in Mexico and Spain: A related but under-investigated development
There is a consensus within Mexican accounting historiography regarding widespread use of double entry bookkeeping by the end of the 19th Century in the realm of both private and public enterprise. However, there is conflicting and even contradictory claims as to when exactly this technique arrived to the viceroyalty of New Spain (present day Mexico) as well as its diffusion during the colonial era. In this article we address this conflict while putting forward the idea that the history of ‘modern’ accounting practice in Latin America should be framed by developments in its former colonial power. We offer the analysis of primary and secondary source material to support the view that there was continuity in the use of double entry in Spain and therefore, the so called ‘period of silence and apparent oblivion’ seems limited to the production of indigenous accounting thought (as expressed in the production of bibliographic material such as manuals and textbooks). We conclude that the history of Latin America accounting should be wary of extrapolating everyday practice by interpreting bibliographic material and proceed by examining surviving company documents as well as informal educational practices amongst organisations based in the metropolis and its then colonies.double entry, diffusion of accounting systems, knowledge transfer, Mexico (New Spain), Spain
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