“Flatten” file names in the terminal

I am often dealing with folders with lots of files with weird file names. Spaces, capital letters, and so on, often cause problems. Instead of manually fixing such file names, here is a quick one-liner (found here) that can be run in the terminal (at least on Ubuntu) to solve the problem:

rename 'tr/ A-Z/-a-z/' -- *

It is based on a simple regular expression, replacing any spaces with hyphens, and changing any capital letters to lower case.

Some thoughts on microphones for streaming and recording

Many people have asked me about what types of microphones to use for streaming and recording. This is really a jungle, with lots of devices and things to think about. I have written some blog posts about such things previously, such as tips for doing Skype job interviews, testing simple camera/mic solutions, running a Hybrid Disputation, and how to work with plug-in-power microphones.

Earlier today I held a short presentation about microphones at RITMO. This was during our informal Food & Paper lunch seminar, where people eat their lunch while listening to presentations about different topics (usually something academic, but sometimes also other things). Here is a cut-down version of the presentation:

The presentation starts by drawing up the main things to think about: microphones and speakers and the environments that people use these devices within. When we stream or record, we don’t really control other people’s speakers and environments. So the two things we should think about are (1) the microphone we use and (2) the environment we are in.

A very brief summary of microphones, speakers, and room acoustics.

The make a long story short, here are my general advice:

  • Place yourself in a “dry” and quiet space, if possible. A small room with carpets and curtains is much better than a big and empty space.
  • A headset with a boom microphone will usually give the best sound overall, without feedback, and allow you to move your head around. I have many USB headsets from Logitech, Jabra, and Poly, and all of them are fine. The more expensive ones are more comfortable to wear, but the sound quality doesn’t really differ that much. I generally try to avoid Bluetooth headsets since they need to be charged and paired to function. If you can live with a cable, you will get better sound for a lower price.
  • A “podcast-style” condenser microphone will give a more pleasant and radio-like sound. You can also avoid sitting with headphones on all the time, which is very tiresome after some hours. However, condenser microphones are usually relatively large, need a stand, and you may get into feedback problems. There are many options here, but I have been very positively surprised by this cheap Marantz USB microphone.
  • A lavalier microphone is the best choice for making video recordings. They are small, pick up sounds nicely, and some (like the Røde Smartlav+) can be connected directly to a mobile phone or laptop.

There are always better, more expensive, and more complicated solutions out there. However, I am very impressed by some of the newest products that have arrived on the market. The products highlighted above are reasonably priced and will greatly improve the audio of both streaming and recording.

Visualising a Bach prelude played on Boomwhackers

I came across a fantastic performance of a Bach prelude played on Boomwhackers by Les Objets Volants.

It is really incredible how they manage to coordinate the sticks and make it into a beautiful performance. Given my interest in the visual aspects of music performance, I reached for the Musical Gestures Toolbox to create some video visualisations.

I started with creating an average image of the video:

Average image of the video.

This image is not particularly interesting. The performers moved around quite a bit, so the average image mainly shows the stage. An alternative spatial summary is the creation of a keyframe history image of the video file. This is created by extracting the keyframes of the video (approximately 50 frames) and combining these into one image:

Keyframe history image.

The keyframe history image summarizes how the performers moved around on stage and explained the spatial distribution of activity over time. But to get more into the temporal distribution of motion, we need to look at a spatiotemporal visualization. This is where motiongrams are useful:

Motiongram of vertical motion (time from left to right)
Motiongram of vertical motion (time from left to right)
Motiongram of horizontal motion (time from top to bottom)
Motiongram of horizontal motion (time from top to bottom)

If you click on the images above, you can zoom in to look at the visual beauty of the performance.

Analyzing a double stroke drum roll

Yesterday, PhD fellow Mojtaba Karbassi presented his research on impedance control in robotic drumming at RITMO. I will surely get back to discussing more of his research later. Today, I wanted to share the analysis of one of the videos he showed. Mojtaba is working on developing a robot that can play a double stroke drum roll. To explain what this is, he showed this video he had found online, made by John Wooton:

The double stroke roll is a standard technique for drummers, but not everyone manages to perform it as evenly as in this example. I was eager to have a look at the actions in a little more detail. We are currently beta-testing the next release of the Musical Gestures Toolbox for Python, so I thought this video would be a nice test case.

Motion video

I started the analysis by extracting the part of the video where he is showing the complete drum roll. Next, I generated a motion video of this segment:

This is already fascinating to look at. Since the background is removed, only the motion is visible. Obviously, the framerate of the video is not able to capture the speed that he plays with. I was therefore curious about the level of detail I could achieve in the further analysis.

Audio visualization

Before delving into the visualization of the video file, I made a spectrogram of the sound:

If you are used to looking at spectrograms, you can quite clearly see the change in frequency as the drummer is speeding up and then slowing down again. However, a tempogram of the audio is even clearer:

Here you can really see the change in both the frequency and the onset strength. The audio is sampled at a much higher frequency (44.1 kHz) than the video (25 fps). Is it possible to see some of the same effects in the motion?


I then moved on to create a motiongram of the video:

There are two problems with this motiongram. First, the recording is composed of alternating shots from two different camera angles. These changes between shots can clearly be seen in the motiongram (marked with Camera 1 and 2). Second, this horizontal motiongram only reveals the vertical motion in the video image. Since we are here averaging over each row in the image, the motiongram shows both the left and right-hand motion. For such a recording, it is, therefore, more relevant to look at the vertical motiongram, which shows the horizontal motion:

In this motiongram, we can more clearly see the patterns of each hand. Still, we have the problem of the alternating shots. If we “zoom” in on the part called Camera 2b, it is possible to see the evenness of the motion in the most rapid part:

I also find it fascinating to “zoom” in on the part called Camera 2c, which shows the gradual slow-down of motion:

Finally, let us consider the slowest part of the drum roll (Camera 1d):

Here it is possible to see the beauty of the double strokes very clearly.

Convert between video containers with FFmpeg

In my ever-growing collection of smart FFmpeg tricks, here is a way of converting from one container format to another. Here I will convert from a QuickTime (.mov) file to a standard MPEG-4 (.mp4), but the recipe should work between other formats too.

If you came here to just see the solution, here you go:

ffmpeg -i infile.mov -acodec copy -vcodec copy outfile.mp4

In the following I will explain everything in a little more detail.

Container formats

One of the confusing things about video files is that they have both a container and a compression format. The container is often what denotes the file suffix. Apple introduced the .mov format for QuickTime files and Microsoft used to use .avi files.

Nowadays, there seems to a converge towards using MPEG containers and .mp4 files. However, both Apple and Microsoft software (and others) still output other formats. This is confusing and can also lead to various playback issues. For example, many web browsers are not able to play these formats natively.

Compression formats

The compression format denotes how the video data is organized on the inside of a container. Also, here there are many different formats. The most common today is to use the H.264 format for video and AAC for audio. These are both parts of the MPEG-4 standard and can be embedded in .mp4 containers. However, both H.264 and AAC can also be embedded in other containers, such as .mov and .avi files.

The important thing to notice is that both .mov and .avi files may contain H.264 video and AAC audio. In those cases, the inside of such files is identical to the content of a .mp4 file. But since the container is different, it may still be unplayable in certain software. That is why I would like to convert from one container format to another. In practice that means converting from .mov or .avi to .mp4 files.

Lossless conversion

There are many ways of converting video files. In most cases, you would end up with a lossy conversion. That means that the video content will be altered. The file size may be smaller, but the quality may also be worse. The general rule is that you want to compress a file as few times as possible.

For all sorts of video conversion/compression jobs, I have ended up turning to FFmpeg. If you haven’t tried it already, FFmpeg is a collection of tools for doing all sorts of audio/video manipulations in the terminal. Working in the terminal may be intimidating at first, but you will never look back once you get the hang of it.

Converting a file from .mov to .mp4 is as simple as typing this little command in a terminal:

ffmpeg -i infile.mov outfile.mp4

This will change from a .mov container to a .mp4 container, which is what we want. But it will also (probably) re-compress the video. That is why it is always smart to look at the content of your original file before converting it. You can do this by typing:

ffmpeg -i infile.mov

For my example file, this returns the following metadata:

    major_brand     : qt  
    minor_version   : 0
    compatible_brands: qt  
    creation_time   : 2016-08-10T10:47:30.000000Z
    com.apple.quicktime.make: Apple
    com.apple.quicktime.model: MacBookPro11,1
    com.apple.quicktime.software: Mac OS X 10.11.6 (15G31)
    com.apple.quicktime.creationdate: 2016-08-10T12:45:43+0200
  Duration: 00:00:12.76, start: 0.000000, bitrate: 5780 kb/s
    Stream #0:0(und): Video: h264 (Main) (avc1 / 0x31637661), yuv420p(tv, bt709), 1844x1160 [SAR 1:1 DAR 461:290], 5243 kb/s, 58.66 fps, 60 tbr, 6k tbn, 50 tbc (default)
      creation_time   : 2016-08-10T10:47:30.000000Z
      handler_name    : Core Media Video
      encoder         : H.264
    Stream #0:1(und): Audio: aac (LC) (mp4a / 0x6134706D), 44100 Hz, stereo, fltp, 269 kb/s (default)
      creation_time   : 2016-08-10T10:47:30.000000Z
      handler_name    : Core Media Audio

There is quite a lot of information there, so we need to look for the important stuff. The first line we want to look for is the one with information about the video content:

Stream #0:0(und): Video: h264 (Main) (avc1 / 0x31637661), yuv420p(tv, bt709), 1844x1160 [SAR 1:1 DAR 461:290], 5243 kb/s, 58.66 fps, 60 tbr, 6k     

Here we can see that this .mov file contains a video that is already compressed with H.264. Another thing we can see here is that it is using a weird pixel format (1844×1160). The bit rate of the file is 5243 kb/s, which tells something about how large the file will be in the end. And it is also interesting to see that it is using a framerate of 58.66 fps, which is also a bit odd.

Similarly, we can look at the content of the audio stream of the file:

Stream #0:1(und): Audio: aac (LC) (mp4a / 0x6134706D), 44100 Hz, stereo, fltp, 269 kb/s (default)

Here we can see that the audio is already compressed with AAC at a standard sampling rate of 44.1 kHz and at a more nonstandard bit rate of 269 kb/s.

The main point of investigating the file before we do the conversion is to avoid re-compressing the content of the file. After all, the content is already in the right formats (H.264 and AAC) even though it is in an unwanted container (.mov).

Today’s little trick is how to convert from one format to another without modifying the content of the file, only the container. That can be achieved with the code shown on top:

ffmpeg -i original.mov -acodec copy -vcodec copy outfile.mp4

There are several benefits of doing it this way:

  1. Quality. Avoiding an unnecessary re-compression of the content, which would only degrade the content.
  2. Preserve the pixel size, sampling rates, etc. of the originals. Most video software will use standard settings for these. I often work with various types of non-standard video files, so it is nice to preserve this information.
  3. Save time. Since no re-compression is needed, we only copy content from one container to another. This is much, much faster than re-compressing the content.

All in all, this long explanation of a short command may help to improve your workflows and save some time.