Impact of automated action labeling in classification of human actions in RGB-D videos

For many applications it is important to be able to detect what a human is currently doing. This ability is useful for applications such as surveillance, human computer interfaces, games and healthcare. In order to recognize a human action, the typical approach is to use manually labeled data to perform supervised training. This paper aims to compare the performance of several supervised classifiers trained with manually labeled data versus the same classifiers trained with data automatically labeled. In this paper we propose a framework capable of recognizing human actions using supervised classifiers trained with automatically labeled data in RGB-D videos.info:eu-repo/semantics/publishedVersio

Predicting human activities in sequences of actions in RGB-D videos

In our daily activities we perform prediction or anticipation when interacting with other humans or with objects. Prediction of human activity made by computers has several potential applications: surveillance systems, human computer interfaces, sports video analysis, human-robot-collaboration, games and health-care. We propose a system capable of recognizing and predicting human actions using supervised classifiers trained with automatically labeled data evaluated in our human activity RGB-D dataset (recorded with a Kinect sensor) and using only the position of the main skeleton joints to extract features. Using conditional random fields (CRFs) to model the sequential nature of actions in a sequence has been used before, but where other approaches try to predict an outcome or anticipate ahead in time (seconds), we try to predict what will be the next action of a subject. Our results show an activity prediction accuracy of 89.9% using an automatically labeled dataset.info:eu-repo/semantics/acceptedVersio

Human activity recognition from automatically labeled data in RGB-D videos

Human Activity Recognition (HAR) is an interdisciplinary research area that has been attracting interest from several research communities specialized in machine learning, computer vision, medical and gaming research. The potential applications range from surveillance systems, human computer interfaces, sports video analysis, digital shopping assistants, video retrieval, games and health-care. Several and diverse approaches exist to recognize a human action. From computer vision techniques, modeling relations between human motion and objects, marker-based tracking systems and RGB-D cameras. Using a Kinect sensor that provides the position of the main skeleton joints we extract features based solely on the motion of those joints. This paper aims to compare the performance of several supervised classifiers trained with manually labeled data versus the same classifiers trained with data automatically labeled. We propose a framework capable of recognizing human actions using supervised classifiers trained with automatically labeled data.info:eu-repo/semantics/acceptedVersio

Automatic human activity segmentation and labeling in RGBD videos

Human activity recognition has become one of the most active research topics in image processing and pattern recognition. Manual analysis of video is labour intensive, fatiguing, and error prone. Solving the problem of recognizing human activities from video can lead to improvements in several application fields like surveillance systems, human computer interfaces, sports video analysis, digital shopping assistants, video retrieval, gaming and health-care. This paper aims to recognize an action performed in a sequence of continuous actions recorded with a Kinect sensor based on the information about the position of the main skeleton joints. The typical approach is to use manually labeled data to perform supervised training. In this paper we propose a method to perform automatic temporal segmentation in order to separate the sequence in a set of actions. By measuring the amount of movement that occurs in each joint of the skeleton we are able to find temporal segments that represent the singular actions.We also proposed an automatic labeling method of human actions using a clustering algorithm on a subset of the available features.info:eu-repo/semantics/acceptedVersio

Measurement of the 0.511 MeV gamma ray line from the Galactic Center

The detection of the 0.511 MeV electron positron annihilation line coming from the Galactic Center to provide the means to estimate the rate of positron production and to test some theoretical sources of positrons is addressed. The results of the measurements of the 0.511 MeV line flux made with a gamma ray experiment on board a stratospheric balloon are presented. The detector field of view looked at the galactic longitude range -31 deg l(II) +41 deg. The observed flux is 0.0067 (+ or - 0.0005) photons 1/cm(2)5 which is in very good agreement with the expected flux when assuming that the Galactic Center is a line source emitting uniformly

Proposta de redesign de caiaque para a escola municipal de remo de Volta Redonda-RJ

Este trabalho apresenta a proposta de redesign de um caiaque desenvolvido especificamente para a cidade de Volta Redonda. O município oferece aulas gratuitas de remo que acontecem no Parque Aquático da Ilha São João. Esse redesign propõe um novo caiaque, que sugere o uso de compósitos poliméricos reforçados com fibras de côco que oferecem propriedades melhores ou comparáveis com muitos materiais convencionais. Essas fibras são superiores ambientalmente comparados às fibras sintéticas, especialmente à fibra de vidro. Neste trabalho utilizou-se da semiótica para aplicar o símbolo que dá nome à cidade: a volta do rio Paraíba do Sul. Esse símbolo foi aplicado na parte superior frontal (proa) servindo também como proteção para que não entre água no cockpit do caiaque. Além da semiótica, a cor é um elemento essencial do design capaz de gerar reações associativas. A aplicação do amarelo gera sensação de movimento, ação; é uma cor brilhante e alegre que lembra as estações mais quentes do ano. O azul – usado no símbolo e no fundo do caiaque – remete a água, à cor do céu. (AMBROSE, G.; HARRIS, P., 2009). O uso destas duas cores tem ligação direta com o esporte, principalmente para esse projeto, em que sua prática se dá em ambiente aquático

Assessment of the Impact of Potential Tetracycline Exposure on the Phenotype of Aedes aegypti OX513A: Implications for Field Use

Aedes aegypti is the primary vector of dengue fever, a viral disease which has an estimated incidence of 390 million infections annually. Conventional vector control methods have been unable to curb the transmission of the disease. We have previously reported a novel method of vector control using a tetracycline repressible self-limiting strain of Ae. aegypti OX513A which has achieved >90% suppression of wild populations.We investigated the impact of tetracycline and its analogues on the phenotype of OX513A from the perspective of possible routes and levels of environmental exposure. We determined the minimum concentration of tetracycline and its analogues that will allow an increased survivorship and found these to be greater than the maximum concentration of tetracyclines found in known Ae. aegypti breeding sites and their surrounding areas. Furthermore, we determined that OX513A parents fed tetracycline are unable to pre-load their progeny with sufficient antidote to increase their survivorship. Finally, we studied the changes in concentration of tetracycline in the mass production rearing water of OX513A and the developing insect.Together, these studies demonstrate that potential routes of exposure of OX513A individuals to tetracycline and its analogues in the environment are not expected to increase the survivorship of OX513A

Análise exploratória das taxas de mortalidades das diferentes categorias de bovinos de corte.

O desempenho zootécnico da pecuária tradicional do Pantanal situa-se abaixo da média nacional, com baixos índices de natalidade e desmama, além de alta taxa de mortalidade, principalmente em categorias de animais jovens. Com objetivo de aumentar a eficiência, por meio da minimização das taxas de mortalidade foram acompanhadas em 2017, as causas de mortalidade das diferentes categorias na fazenda Bodoquena Ltda, situada no município de Miranda, MS