Working with Vantrue X2 Dashcam and Dashcam Viewer

Dashcams are becoming more and more affordable as they become easier to manufacture and their use becomes more ubiquitous. I had previously used a Rexing R2 dashcam but was looking to get into something with more robust data collection capability. The Rexing R2 served as a good initial exposure for dashcam operation and the associated workflow (storage, editing). I was able to incorporate dashcam operation into my working theory of data curation in that any dashcam data that was collected, even it is not inherently valuable, may prove valuable in the future, and thus, should be stored indefinitely.


As a quick example of the usefulness of this kind of dashcam ubiquity, we can look to the meteor that touched down near Chelyabinsk, Russia in February 2013. Almost all of the footage is from dashcams, which are mandatory in the country to prevent insurance fraud, and CCTVs. I’m not saying I’m likely to catch a meteor coming down to Earth and it’s my responsibility as a dashcam owner to be prepared for that moment, but I’d rather be caught with it on rather than off. The footage can also become the medium for other creative expression.

I enjoy working with the footage, speeding it up and putting it alongside music. Driving is something I enjoy and editing driving footage provides a similar satisfaction. Unfortunately, the Rexing R2 and its fish-eyed convex lens was destined to end badly. The lens protruded beyond the safety of the bezel and all it took was one instance of accidentally setting it lens-side down on an abrasive surface for the lens to be slightly cracked, enough to blemish the picture.

Finding a camera which was immune to this kind of operator error was my first priority. Also important was the incorporation of a GPS unit with exportable data. I find a reasonable solution in the Vantrue X2. It was a steal on Amazon for $99, though seems to be out of stock now. It comes out of the box with 2K filming capability, expertly tailored night vision, 64GB microSD support, and an optional GPS mount. This cam checked all the boxes. Two days later I had it installed and took it for a test drive.

A couple things to consider right off the bat; I do quite a bit of driving on average and I’m not one who wants to dismount the camera and export all the footage several times a week. I also thought it would be irresponsible, since I’m storing this footage for whatever future opportunities might arise, to film in less than the full 2K resolution of the camera’s capability. 64GB SD card capability becomes just “OK” at this point, storing between 6 and 7 hours of data before needing to be hooked up to the computer and moved over. 128 or greater might be something I look for in the future, although I’m definitely not in the market for another camera. The 6 hours hasn’t been a problem except for a handful of times I’ve been driving long distances and found myself needing to offload the footage temporary on a device before delivering it to the storage server. However, the average user will not have these problems if they’re not meticulously hoarding this data. The camera has functionality that allows it to overwrite previous footage when it becomes full. Relying on this rolling recording will always assure you have the last 6 hours of driving footage, no maintenance required.

Armed with the camera and GPS mount, I was ready to collect the data, which came naturally over the following months. The next step in this geographic exploration was to incorporate this data in some sort of map. This led me to the Dashcam Viewer by Earthshine Software. This program extracts the GPS data from the videos, plots them on a map, and allows you to cartographically exam your driving. Dashcam Viewer is available for Windows and Mac. Sadly, there is not an official Linux version, although I haven’t tried emulating it on a Linux machine with Wine.




The first video I thought to make was a realtime video with two maps of different scale, showing where the vehicle is in relation to the surroundings that might not be visible on film. Dashcam viewer includes lines that show differences in relative speed which is a nice touch, and saves time compared to crunching this data manually in something like ArcGIS.

Capturing the map footage required a little ingenuity. I couldn’t save the video of the Dashcam coordinate route so I thought capturing video of the desktop then cropping it to the window in question would the easiest route to get a result. The finer details could be ironed out afterwards. I was able to create the two cropped videos of the maps and using the Filmora editor, was able to combine them with the actual footage. A little editing flare and some music was all it took to combine this rough draft, which served as a proof of concept for future projects.



Next I wanted to move onto timelapse videos so these new map perspectives could be incorporated. The length of the editing process is something I’m still trying to reduce with this workflow. Capturing the 2 maps in realtime using Xsplit to capture the desktop adds 2 times the length of the original footage to the process. For the next project, I wanted to use a 4 hour segment of films. This would require 8 hours of desktop capture, not acceptable for a productive workflow, but for what I am doing in this early proof-of-concept stage, getting the results is more important than the workflow.

I started running into limitation in the Filmora video editor. Editing with multiple video sources was limited, and I couldn’t export the final production in glorious 2K resolution due to the 1080p limit. Filmora isn’t native to Linux which is the ecosystem I’m trying to move all my production towards. Wine emulation is poor. For the future, I’m looking towards Da Vinci Resolve by BlackMagic. This, I assume, is an intermediate video editing application where Filmora is focus more on entry level editing.

The idea for the second project using the new dashcam was based around a 4 hour trip. I captured all the media. Moved it over to my Windows machine to edit with Filmora. To make the editing process easier, I focused on one source at a time. First, I merged all the dashcam footage into one video. This machine is working with a Q6950 processor so all rendering had to be done overnight. Once the dashcam footage was one video, it was easily muted sped up by a factor of ten, then rendered again. This gave me finalized footage I wouldn’t have to edit when piecing all the sources together.

I then booted up dashcam viewer and started the desktop capture of the maps in realtime. This took over 8 hours for both maps. Once the capture was complete, they were put through some quick editing so post-production would just be piecing the sources together. They were sped up 10x and rendered individually with custom resolutions, so they could sit on top of the original footage seamlessly.

The first map was set to “follow” the GPS signal at a small scale. The second map would show a majority of the trip and often the starting point and destination in the same frame. These provided two different perspectives for the footage in case the viewer wants supplementary geographic information.

Syncing all the footage was something that turned out to be more complicated than expected. I originally wanted the final editing procedure to be just piecing together the three sources, the dashcam footage, and the two maps. However, the maps were often out of sync with the footage, and had to be adjusted manually every few minutes. This led to chopping up the footage, creating errors in the maps halfway, thanks to Filmora and operator errors.

Post production included adding the music, adding the song information, and fading in and out where appropriate. The final product is not perfect, as there are map errors in the middle of the video and at the end, but I’m happy with how the workflow and the product ended up.


In the future, I hope to choose a different editor, and see if I can find an additional way to capture and render the maps, with a focus on speed of production. I’d love to find other ways to incorporate GPS information like bearing and speed into the video. Until then, it’s off to add to the every growing collection of dashcam footage.

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