We have three papers from our fourMs group at this year’s NIME conference in Daejeon. The first one was presented today by Ståle Skogstad, and is based on his work on trying minimize the delay when filtering motion capture data. Title Filtering motion capture data for real-time applications Links: Paper (PDF) Project page Max/MSP implementation Abstract: In this paper we present some custom designed filters for real-time motion capture applications. Our target application is motion controllers, i.

I will participate in a motion capture workshop at the Norwegian University of Science and Technology (NTNU) tomorrow. My contribution will consist of the following: Lecture: Introduction to motion capture (in music analysis and performance) Demo 1: Working with video analysis using the Musical Gestures Toolbox Demo 2: The Xsens MVN BioMech mobile mocap suit Workshop: Analysis and performance with Wii controllers, Phidgets accelerometers and Kinect Below are various resources.

I spend a lot of time walking around the city with my daughter these days, and have been wondering how much I move and how the movement is distributed over time. To answer these questions, and to try out a method for easy and cheap motion capture, I decided to record today’s walk to the playground. I could probably have recorded the accelerometer data in my phone, but I wanted to try an even more low-tech solution: an audio recorder.