Last week, I watched the total solar eclipse from eastern Tennessee, across the Tennessee River from the Watts Bar Nuclear Plant. I was originally planning on watching it from the mountains on the border between Tennessee and North Carolina, but the cloud cover forecast the day of predicted much better weather farther west.
With a total solar eclipse in the continental United States coming up next month, I purchased a solar filter for my telephoto lens. Unfortunately, this OD 5.0 solar filter, which is required for safe optical viewing is much too dark for optimal photography. This led me to purchase a sheet of OD 3.8 photographic solar filter film (from Europe, since no one seems to sell it in the United States). This film requires a holder, and while I could have made a paper holder, I opted to 3D print one instead. By making the inside diameter slightly larger than the lens’ outside diameter, it fits in place snuggly, and is much sturdier than a paper holder. The film is cut to size and sandwiched between the two 3D printed segments using double-sided tape. The screws I used in the first holder proved unnecessary, so I left them out on the second holder I made.
Due to extensive trail work over the past two years, new maps of Camp Workcoeman were needed. Furthermore, the Connecticut statewide spring 2016 orthoimagery was recently released, provide a new data source for updating buildings and land cover. As with my previous mapping, I walked the rerouted trails using a SkyTraq-based receiver that records raw carrier-phase and pseudorange data and post-processed the data using RTKLIB and CORS data from the nearby CTWI site in Winchester. In revising the trail center map, I took the oppertunity to improve it with additional hand-placed labels1 and various minor tweaks.
Updated maps are on the campworkcoeman.org maps page. The data is bundled in the Camp Workcoeman Map App. The web app has been updated, and an update to the Android version, which is fully-offline, is forthcoming.
Auto-label placement still has a long way to go… ↩
Recently, I’ve been looking at various fiducial markers for computer vision applications. While some of these markers, such as AprilTags, have readily available reference implementations, others have no published code. While one of the markers I was looking at, Pi-Tags, does not have a reference implementation, it does have a third party implementation in the form of a Robot Operating System (ROS) module, cob_fiducials; this is great for robotics applications using ROS, but problematic otherwise. Since I wasn’t interested in using the detector with ROS, I separated it out into a standalone library. Additionally, I modified the detector to add a function that just returns the image pixel coordinates of the detected markers instead of calculating their poses, and added the ellipse refinement step1 that was mentioned in the Pi-Tag paper.2
Ouellet, Jean-Nicolas, and Patrick Hébert. “Precise ellipse estimation without contour point extraction.” Machine Vision and Applications 21, no. 1 (2009): 59. ↩
Bergamasco, Filippo, Andrea Albarelli, and Andrea Torsello. “Pi-tag: a fast image-space marker design based on projective invariants.” Machine vision and applications 24, no. 6 (2013): 1295-1310. ↩
Although the OSD3358 system-in-package, the so-called BeagleBone on a Chip, is a BGA package, it turns out that it’s surprisingly easy to solder. Using a stencil, solder paste, and a hot plate, it ended up being easier to solder than some QFN and fine pitch leaded packages I’ve soldered via the same method, since the OSD3358’s ball pitch is wider and the PCB pads have solder resist between them.
Unfortunately, I didn’t take any photos while soldering them.
