Browsing Institutt for informatikk by Author "Jensenius, Alexander Refsum"

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  • Robotics and Intelligent Systems at University of Oslo 
    Tørresen, Jim; Glette, Kyrre Harald; Jensenius, Alexander Refsum; Furuholmen, Marcus (Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2009)
    The Robotics and Intelligent Systems group conducts research in the interdisciplinary field of robotics, machine learning, reconfigurable hardware and sensing human actions. The group is affiliated to the Department of ...
  • Searching for Cross-Individual Relationships between Sound and Movement Features using an SVM Classi er 
    Nymoen, Kristian; Jensenius, Alexander Refsum; Tørresen, Jim; Glette, Kyrre Harald; Skogstad, Ståle Andreas van Dorp (Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2010)
    In this paper we present a method for studying relationships between features of sound and features of movement. The method has been tested by carrying out an experiment with people moving an object in space along with ...
  • SoundSaber - A Motion Capture Instrument 
    Nymoen, Kristian; Skogstad, Ståle Andreas van Dorp; Jensenius, Alexander Refsum (Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2011)
    The paper presents the SoundSaber - a musical instrument based on motion capture technology. We present technical details of the instrument and discuss the design development process. The SoundSaber may be used as an example ...
  • A Statistical Approach to Analyzing Sound Tracings 
    Nymoen, Kristian; Tørresen, Jim; Godøy, Rolf Inge; Jensenius, Alexander Refsum (Chapter / Bokkapittel / AcceptedVersion; Peer reviewed, 2012)
    This paper presents an experiment on sound tracing, meaning an experiment on how people relate motion to sound. 38 participants were presented with 18 short sounds, and instructed to move their hands in the air while acting ...
  • A Study of the Noise-Level in Two Infrared Marker-Based Motion Capture Systems 
    Jensenius, Alexander Refsum; Nymoen, Kristian; Skogstad, Ståle Andreas van Dorp; Voldsund, Arve (Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2012)
    With musical applications in mind, this paper reports on the level of noise observed in two commercial infrared marker-based motion capture systems: one high-end (Qualisys) and one affordable (OptiTrack). We have tested ...
  • Tool or Actor? Expert Improvisers' Evaluation of a Musical AI “Toddler” 
    Erdem, Cagri; Wallace, Benedikte; Glette, Kyrre; Jensenius, Alexander Refsum (Journal article / Tidsskriftartikkel / PublishedVersion; Peer reviewed, 2022)
    Abstract In this article, we introduce the coadaptive audiovisual instrument, CAVI. This instrument uses deep learning to generate control signals based on muscle and motion data of a performer's actions. The ...
  • A Toolbox for Storing and Streaming Music-related Data 
    Nymoen, Kristian; Jensenius, Alexander Refsum (Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2011)
    Simultaneous handling and synchronisation of data related to music, such as score annotations, MIDI, video, motion descriptors, sensor data, etc. requires special tools due to the diversity of this data. We present a toolbox ...
  • Towards Playing in the 'Air': Modeling Motion-Sound Energy Relationships in Electric Guitar Performance Using Deep Neural Networks 
    Erdem, Cagri; Lan, Qichao; Fuhrer, Julian; Martin, Charles Patrick; Tørresen, Jim; Jensenius, Alexander Refsum (Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2020)
    In acoustic instruments, sound production relies on the interaction between physical objects. Digital musical instruments, on the other hand, are based on arbitrarily designed action--sound mappings. This paper describes ...
  • Using IR Optical Marker Based Motion Capture for Exploring Musical Interaction 
    Skogstad, Ståle Andreas van Dorp; Jensenius, Alexander Refsum; Nymoen, Kristian (Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2010)
    The paper presents a conceptual overview of how optical infrared marker based motion capture systems (IrMoCap) can be used in musical interaction. First we present a review of related work of using IrMoCap for musical ...
  • Wireless Sensor Data Collection based on ZigBee Communication 
    Tørresen, Jim; Renton, Eirik; Jensenius, Alexander Refsum (Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2010)
    This paper presents a comparison of different configurations of a wireless sensor system for capturing human motion. The systems consist of sensor elements which wirelessly transfers motion data to a receiver element. The ...