Questões de Concurso Público ITAIPU BINACIONAL 2017 para Profissional de Nível Superior Jr - Computação ou Informática – Sistemas
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Computer that reads body language
Researchers at Carnegie Mellon University’s Robotics Institute have enabled a computer to understand body poses and movements of multiple people from video in real time – including, for the first time, the pose of each individual’s hands and fingers.
Carnegie Mellon University researchers have developed methods to detect the body pose, including facial expressions and hand positions, of multiple individuals. This enables computers to not only identify parts of the body, but to understand how they are moving and positioned.
This new method was developed with the help of the Panoptic Studio, a two-story dome embedded with 500 video cameras. The insights gained from experiments in that facility now make it possible to detect the pose of a group of people using a single camera and a laptop computer.
Yaser Sheikh, associate professor of robotics, said these methods for tracking 2-D human form and motion open up new ways for people and machines to interact with each other, and for people to use machines to better understand the world around them. The ability to recognize hand poses, for instance, will make it possible for people to interact with computers in new and more natural ways, such as communicating with computers simply by pointing at things.
Detecting the nuances of nonverbal communication between individuals will allow robots to serve in social spaces, allowing robots to perceive what people around them are doing, what moods they are in and whether they can be interrupted. A self-driving car could get an early warning that a pedestrian is about to step into the street by monitoring body language. In sports analytics, real-time pose detection will make it possible for computers not only to track the position of each player on the field of play, as is now the case, but to also know what players are doing with their arms, legs and heads at each point in time. The methods can be used for live events or applied to existing videos.
“The Panoptic Studio supercharges our research”, Sheikh said. It now is being used to improve body, face and hand detectors by jointly training them. Also, as work progresses to move from the 2-D models of humans to 3-D models, the facility’s ability to automatically generate annotated images will be crucial.
When the Panoptic Studio was built a decade ago with support from the National Science Foundation, it was not clear what impact it would have, Sheikh said.
“Now, we’re able to break through a number of technical barriers primarily as a result of a grant 10 years ago”, he added. “We’re sharing the code, but we’re also sharing all the data captured in the Panoptic Studio”.
(Disponível: <https://www.sciencedaily.com/releases/2017/07/170706143158.htm>
Com base no texto, considere as seguintes informações:
1. O nome da instituição que desenvolveu a pesquisa.
2. O local onde está situado o estúdio Panoptic.
3. O número de pessoas que serviram como cobaias no experimento.
4. A época em que o estúdio foi construído.
5. A dificuldade de serem encontrados modelos humanos para interagir com computadores.
O texto apresenta as informações contidas nos itens:
Computer that reads body language
Researchers at Carnegie Mellon University’s Robotics Institute have enabled a computer to understand body poses and movements of multiple people from video in real time – including, for the first time, the pose of each individual’s hands and fingers.
Carnegie Mellon University researchers have developed methods to detect the body pose, including facial expressions and hand positions, of multiple individuals. This enables computers to not only identify parts of the body, but to understand how they are moving and positioned.
This new method was developed with the help of the Panoptic Studio, a two-story dome embedded with 500 video cameras. The insights gained from experiments in that facility now make it possible to detect the pose of a group of people using a single camera and a laptop computer.
Yaser Sheikh, associate professor of robotics, said these methods for tracking 2-D human form and motion open up new ways for people and machines to interact with each other, and for people to use machines to better understand the world around them. The ability to recognize hand poses, for instance, will make it possible for people to interact with computers in new and more natural ways, such as communicating with computers simply by pointing at things.
Detecting the nuances of nonverbal communication between individuals will allow robots to serve in social spaces, allowing robots to perceive what people around them are doing, what moods they are in and whether they can be interrupted. A self-driving car could get an early warning that a pedestrian is about to step into the street by monitoring body language. In sports analytics, real-time pose detection will make it possible for computers not only to track the position of each player on the field of play, as is now the case, but to also know what players are doing with their arms, legs and heads at each point in time. The methods can be used for live events or applied to existing videos.
“The Panoptic Studio supercharges our research”, Sheikh said. It now is being used to improve body, face and hand detectors by jointly training them. Also, as work progresses to move from the 2-D models of humans to 3-D models, the facility’s ability to automatically generate annotated images will be crucial.
When the Panoptic Studio was built a decade ago with support from the National Science Foundation, it was not clear what impact it would have, Sheikh said.
“Now, we’re able to break through a number of technical barriers primarily as a result of a grant 10 years ago”, he added. “We’re sharing the code, but we’re also sharing all the data captured in the Panoptic Studio”.
(Disponível: <https://www.sciencedaily.com/releases/2017/07/170706143158.htm>
Computer that reads body language
Researchers at Carnegie Mellon University’s Robotics Institute have enabled a computer to understand body poses and movements of multiple people from video in real time – including, for the first time, the pose of each individual’s hands and fingers.
Carnegie Mellon University researchers have developed methods to detect the body pose, including facial expressions and hand positions, of multiple individuals. This enables computers to not only identify parts of the body, but to understand how they are moving and positioned.
This new method was developed with the help of the Panoptic Studio, a two-story dome embedded with 500 video cameras. The insights gained from experiments in that facility now make it possible to detect the pose of a group of people using a single camera and a laptop computer.
Yaser Sheikh, associate professor of robotics, said these methods for tracking 2-D human form and motion open up new ways for people and machines to interact with each other, and for people to use machines to better understand the world around them. The ability to recognize hand poses, for instance, will make it possible for people to interact with computers in new and more natural ways, such as communicating with computers simply by pointing at things.
Detecting the nuances of nonverbal communication between individuals will allow robots to serve in social spaces, allowing robots to perceive what people around them are doing, what moods they are in and whether they can be interrupted. A self-driving car could get an early warning that a pedestrian is about to step into the street by monitoring body language. In sports analytics, real-time pose detection will make it possible for computers not only to track the position of each player on the field of play, as is now the case, but to also know what players are doing with their arms, legs and heads at each point in time. The methods can be used for live events or applied to existing videos.
“The Panoptic Studio supercharges our research”, Sheikh said. It now is being used to improve body, face and hand detectors by jointly training them. Also, as work progresses to move from the 2-D models of humans to 3-D models, the facility’s ability to automatically generate annotated images will be crucial.
When the Panoptic Studio was built a decade ago with support from the National Science Foundation, it was not clear what impact it would have, Sheikh said.
“Now, we’re able to break through a number of technical barriers primarily as a result of a grant 10 years ago”, he added. “We’re sharing the code, but we’re also sharing all the data captured in the Panoptic Studio”.
(Disponível: <https://www.sciencedaily.com/releases/2017/07/170706143158.htm>
Com relação aos anagramas da palavra ITAIPU, identifique como verdadeiras (V) ou falsas (F) as seguintes afirmativas:
( ) Há 360 anagramas distintos.
( ) Há 30 anagramas distintos em que as duas consoantes estão juntas.
( ) Há 24 anagramas que começam e terminam com a letra I.
( ) Há 200 anagramas em que as letras I estão separadas.
Assinale a alternativa que apresenta a sequência correta, de cima para baixo.
Seja T = R2 → R2 uma transformação linear cuja matriz, em relação às bases canônicas, é
Considere as seguintes afirmativas:
1. O núcleo N(T) = {v ∈ R2; Tv = 0 } contém apenas o vetor nulo.
2. A transformação T é sobrejetiva.
3. A transformação T possui dois autovalores distintos.
4. A transformação T é diagonalizável.
Assinale a alternativa correta.
Suponha que as seguintes afirmações são verdadeiras:
• Todos os corredores de maratona são pessoas dedicadas.
• Nenhuma pessoa dedicada é arrogante.
Logo, podemos concluir que:
Com base no diagrama abaixo, considere as seguintes afirmativas relacionadas à notação e ao que esse diagrama representa.
1. A associação entre Lista e Item é do tipo composição e indica que o objeto todo deve gerenciar a criação e destruição de suas partes.
2. A associação entre Item, Música e Vídeo representa uma herança múltipla.
3. tocar() é uma operação polimórfica, significando que, quando uma mensagem é despachada em tempo de execução, uma correspondência é determinada em tempo de execução de acordo com o tipo do objeto.
4. A classe Segue deve possuir atributos ou operações para justificar sua representação como classe de associação.
5. Em tempo de execução, a classe Item precisa ser instanciada para que as classes Música ou Vídeo possam ser utilizadas.
Assinale a alternativa correta
A respeito do Diagrama de Casos abaixo, identifique como verdadeiras (V) ou falsas (F) as seguintes afirmativas:
( ) “Calcular Valores Devidos” será executado sempre que o Auxiliar Administrativo visualizar o relatório de fornecedores.
( ) Ao visualizar o relatório de fornecedores, a geração do gráfico é opcional.
( ) O detalhamento do funcionamento de um caso de uso pode ser feito por meio de uma especificação.
( ) Da forma como está especificado, “Auxiliar Administrativo” não irá executar o caso de uso “Gerar Gráfico”.
( ) Os casos de uso são executados na seguinte sequência: primeiro “Visualizar Relatório de Fornecedores”, depois “Gerar Gráfico” e depois “Calcular Valores Devidos”.
Assinale a alternativa que apresenta a sequência correta, de cima para baixo.
Considere a história de usuário abaixo:
“Como enfermeira, desejo registrar os dados de pressão arterial de um paciente para que eu possa acompanhar as mudanças na pressão arterial ao longo do dia.”
Sobre a forma como essa história de usuário está descrita e como é utilizada no desenvolvimento de software, considere as seguintes afirmativas:
1. Deve possuir a maior quantidade de detalhes possível no início do projeto, mesmo que não seja imediatamente implementada pela equipe de desenvolvimento.
2. Pode ser utilizada em projetos que adotam o método ágil Scrum.
3. Quando descreve uma funcionalidade maior, com menos detalhamento, é chamada de épico.
4. Idealmente, é especificada pelo Scrum Master em um projeto que adota Scrum.
5. No Scrum, o conjunto de histórias de usuário a serem implementadas em um projeto é chamado de Backlog do Desenvolvimento.
Assinale a alternativa correta.
Com relação aos elementos do Scrum, numere a coluna da direita de acordo com sua correspondência com a coluna da esquerda.
1. Sprint.
2. Scrum Diária.
3. Revisão da Sprint.
4. Retrospectiva da Sprint.
( ) Reunião para inspeção das novas funcionalidades implementadas.
( ) Reunião com foco no aprimoramento do processo.
( ) Reunião de 15 minutos para identificação dos impedimentos.
( ) Ciclo completo de desenvolvimento de duração fixa que, ao final, resulta em um incremento de produto.
Assinale a alternativa que apresenta a numeração correta da coluna da direita, de cima para baixo
Conheça nossos planos