Today is New Year’s Eve, and I have done my 365th standstill of the year. I began my year-long #StillStanding project on 1 January this year, and I am happy to report that I managed to conclude the project as planned! A few days were more challenging than others, but I am pleased I made recordings every day. I wrote a blog post after the first 100 days and a video of the first half year.

Today, I am halfway through my year-long #StillStanding project. Not so much has changed since I summed up the first 100 days. I still enjoy the experience, and there are new things to learn every day. Here is a 10-minute video I have recorded that presents the project, explains its rationale, and reflects upon some experiences so far: The biggest challenge moving forward is finding new spaces every day. I have already stood in the most accessible spaces, so I need to spend more time looking for unexplored rooms both at the university and close to my home.

I use a GoPro Max 360-degree camera in my annual #StillStanding project. That means that I also have had an excellent chance to work with GoPro files and try to understand their inner logic. In this blog post, I will summarize some of my findings. What is recorded? Recording “a video” with a GoPro Max results in recording multiple files. For example, each of my daily 10-minute recordings ends up with something like this:

Today marks the 100th day of my annual #StillStanding project. In this blog post, I summarize some of my experiences so far. Endurance Some people questioned whether I would be able to stand still every single day for an entire year. But, hey, it is only ten minutes (out of 1440) per day, and even though my life as a centre director is busy, it is always possible to find time for a standstill sometime during the day.

For my annual Still Standing project, I am recording 360 videos with audio and sensor data while standing still for 10 minutes. I have started exploring how to visualize the sensor data best. Today, I am looking into visualization strategies for 360-degree images. I have written about how to pre-process 360-degree videos from Garmin VIRB and Ricoh Theta cameras previously. The Theta records in a dual fisheye format like this:

Yesterday, I completed my 365 Sound Actions project, during which I recorded one sound action per day as part of preparing for the launch of my book Sound Actions. Today, on 1 January 2023, I start this year’s project: recording myself standing still 10 minutes every day. You can follow the progress on Mastodon. Starting up AMBIENT Although I am happy about completing my sound actions project, I have enjoyed the ritual of doing something every day.

After exploring some visualizations of kayaking, I was eager to see how a similar approach could work for walking. On a trip to the Norwegian mountains, specifically at Haugastøl, situated halfway between Oslo and Bergen, I strapped a GoPro Hero Black 10 on my chest and walked up and down a nearby hill called Storevarden. The walk was approximately 25 minutes up and down, and a fast-forward version of the video can be seen here:

Last year, I wrote about video-based motion analysis of kayaking. Those videos were recorded with a GoPro Hero 8 and I tested some of the video visualization methods of the Musical Gestures Toolbox for Python. This summer I am testing out some 360 cameras for my upcoming AMBIENT project. I thought I should take one of these, a GoPro Max, out for some kayaking in the Oslo fjord. Here are some impressions of the trip (and recording).

I have been doing several long recordings with GoPro cameras recently. The cameras automatically split the recordings into 4GB files, which leaves me with a myriad of files to work with. I have therefore made a script to help with the pre-processing of the files. This is somewhat similar to the script I made to convert MXF files to MP4, but with better handling of the temp file for storing information about the files to merge:

I have previously written about how it is possible to “flatten” a Ricoh Theta+ recording using FFmpeg. Now, I have spent some time exploring how to process some recordings from a Garmin VIRB camera. Some hours of recordings The starting point was a bunch of recordings from our recent MusicLab Copenhagen featuring the amazing Danish String Quartet. A team of RITMO researchers went to Copenhagen and captured the quartet in both rehearsal and performance.

Like many others, I bought a kayak during the pandemic, and I have had many nice trips in the Oslo fiord over the last year. Working at RITMO, I think a lot about rhythm these days, and the rhythmic nature of kayaking made me curious to investigate the pattern a little more. Capturing kayaking motion My spontaneous investigations into kayak motion began with simply recording a short video of myself kayaking.

I take a lot of timelapse shots with a GoPro camera. Usually, I do this with the camera’s photo setting instead of the video setting. That is because I find it easier to delete unwanted pictures from the series that way. It also simplifies selecting individual photos when I want that. But then I need a way to create a timelapse video from the photos easily. Here is an FFmpeg one-liner that does the job:

We just started a new run of our free online course Music Moves. Here we have a tradition of recording wrap-up videos every Friday, in which some of the course educators answer questions from the learners. We have recorded these in many different ways, from using high-end cameras and microphones to just using a handheld phone. We have found that using multiple cameras and microphones is too time-consuming, both in setup and editing.