Recognizing Emotion in Dance

This project aims to examine how a program can detect emotions in a user’s dance
movements, and how this can be utilized in an interactive scenography. The project utilizes machine-learning to predict which emotion is portrayed through the user’s dance moves via a live video-feed. Each classification of the user’s emotion is set to trigger a corresponding graphical animation. The final program manages to create an interactive relation between the user and the scenography’s visual appearance.

Mobileffekter og forstyrrende objekter

This paper concludes that the observed children can be distracted by objects in the classroom, both mobile devices and non-technological
objects. However, mobile devices have certain affordances that intentionally invite
the user to be distracted. Therefore, we conclude that it is effective for schools to
make rules and policies regarding the use of mobile devices. However, it can be
discussed whether we, as adults, can make these statements about the lives of
children, when we have an entirely different lifeworld perspective.


The paper concludes that the use of facial recognition as a surveillance tool is highly problematic, since it allows everyone to be a subject of suspicion. Furthermore, big tech-companies like Facebook and Apple are in a position to possess a huge amount of biometric data, whereby the user loses the ownership of their own personal data. As users we are willingly or without question giving these companies this data by using their technologies every day and by accepting opaque terms of condition.

Netflix’ CO2-udledning

This paper examines the streaming service Netflix and its emission of carbon dioxide. It examines the causes behind Netflix’ emission of carbon dioxide, and to what extent it happens, by looking at the inner workings of how data is transmitted from a data center to a personal device. The purpose of this project is to design a campaign, which can inform young people of the negative effects of streaming on Netflix in the hope that the knowledge will make them change their streaming habits. The iterative design process is used as well as different kinds of qualitative and quantitative methods.

Guerilla Data Collection

Vores projekt gik ud på at lære hvordan dataindsamling og IoT fungerede, og sidenhen bruge denne viden til at indsamle noget selvvalgt data på Ærø, og sætte dette på et kort. I løbet af de sidste to uger, har vi arbejdet med at programmere i Arduino. Vi har fået en forståelse for hvordan data fra den virkelige verden, kan opsamles af en server et helt andet sted. Vi har anvendt denne viden i praksis, og kommet med nogle forskellige bud, på subjektive kort over Ærø.

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