Testing a new descriptor.
Trying a new descriptor, inspired by SURF and SIFT. Want to use gradient instead of Haar transforms of intensity, but with less dimensionality than SURF. Also don’t need rotation/scale invariance, because using incremental tracking.
Learning mathematics is good for the soul
At The n-Category Café David Corfield is talking about mathematical emotions. This is about ‘emotions belonging to mathematical thinking’, specific feeling related to mathematical intuition, meaning and sense of the rightness. In the end he is referencing to spiritual motivation of mathematics. From myself I add that those thoughts are closely related to the last book of Neal Stephenson – Anathem
What I would say to Nokia about mobile AR (if it would listen)
#augmentedreality
I have been struck off the list of the Nokia Augmented Reality co-creation session, so here is a gist of what I was intending to say about AR-friendly mobile devices.
I will not repeat obvious here (requirements for CPU, FPU, RAM etc.) but concentrate on things which are often missed.
I. Hardware side
1. Battery life is the most important thing here. AR applications are eating battery extremely fast – full CPU load, memory access, working camera and on top of it wireless data access, GPS and e-compass.
It’s not realistic to expect dramatic improvement in the battery life in near future, though fuel cells and air-fueled batteries give some hope. If one think short term the dual battery is the most realistic solution. AR-capable devices tend to be quite heavy and not quite slim anyway, so second battery will not make dramatic difference (iPhone could be exception here).
Now how to make maximum out of it? Make batteries hot-swappable with separate slots and provide separate battery charger. If user indoor he/she can remove empty battery and put it on charge while device is running on the second.
2. Heating. Up until now no one was paying attention to the heating of mobile devices, mostly because CPU-heavy apps are very few now (may be only 3d games). AR application produce even more heat than 3d game and device could become quite hot. So heatsinks and heatpumps are on the agenda.
3. Camera. For AR the speed of the camera is more important than the resolution. Speed is the most important factor, slow camera produce blurred images which are extremely hard to process (extract features, edges etc)
Position of the camera. Most of the users are holding device horizontally while using AR. Specific of the mobile AR is that simultaneously user is getting input from the peripheral vision. To produce picture consistent with peripheral vision camera should be in the center of the device, not on the extreme edge like in N900.
Lack of skewing, off-center, radial and rolling shutter distortions of the camera is another factor. In this respect Nokia phone cameras are quite good for now, unlike iPhone.
4. Buttons. Touchscreen is not very helpful to AR, all screen real estate should be dedicated to the environment representation. While it’s quite possible to make completely gesture-driven AR interface buttons are still helpful. There should be at least one easily accessible button on the front panel. N95 with slider out to the right is the almost perfect setup – one big button on front panel and some on the slider on the opposite side. N900 with buttons only on the slider, slider sliding only down and no buttons on the front panel is the example of unhelpful buttons placement.
II. Software side
1. Fragmentation.
Platform fragmentation is the bane of mobile developers. Especially if several new models launched every quarter. One of the reasons of the phenomenal success of iPhone application platform is that there is no fragmentation whatsoever. Whit the huge zoo of models it practically impossible support all that are in the suitable hardware range. That is especially difficult with AR apps, which are closely coupled with camera technical specification, display size and ratio etc. If manufacturers want to make it easy for devs they should concentrate on one AR-friendly line of devices, with binary, or at least source code compatibility between models.
2. Easy access to DSP in API. It would effectively give developer a second CPU.
3. Access to raw data from camera. Why row data from camera are not accessible from ordinary API and only available to selected elite developer houses is a mistery to me. Right now, for example for Symbain OS camera viewfinder convert data to YUV422, from YUV422 to BMP and ordinary viewfinder API have access to BMP only. Quite overhead.
4. API to access internal camera parameters – focus distance etc. Otherwise every device have to be calibrated by developer.
Fake Style at Cosmic Variance
From comments to Fake Stile
Ahmed say:
….
- It is not always clear what emotions the author is trying to communicate, and that sucks. Smileys/emoticons can help here. For e.g., “This is problematic 
” can mean the problem is finally resolving some bigger issue. “This confirms X 
” means a problem is persisting. The smileys will serve as guiding points in the storyline of a paper, so we don’t have to read all of it.
Moving from style to more general regulations:
- Every paper not within the technical grasp of a good undergrad in physics/math/similar should be accompanied with a sister-paper explaining it to (at minimum) such an audience. Just to make sure the author (and the committee!) actually knows what’s going on. String theorists can of course just write an apology or something.
Symbian Signed again.
A discussion is going on at the symbian.org. It looks like a new symbain signed rules are in the work (my guess they will be implemented no earlier than symbian^4). Symbian signed may become cheaper and a new class of publisher ID may become available for anyone with a credit card.
Openness – Maemo vs Android
A great post from coll900 about comparative openness Maemo and Android for developers and users. Maemo designated as a clear win. The one point missing in the original post is a platform fragmentation. Android try to get around fragmentation using Java virtual machine (albeit with non-standard bytecodes). However native code will not be binary transferable between devices. That is especially relevant for augmented reality and other cpu-heavy apps. Here is a question – will Maemo be any better? For some mysterious reasons Nokia afflicted by irresistible drive to fragment it’s own software platform as much as possible. If Nokia manage to gather enough strength of will to keep Maemo on a single but mass-produced device line, like Apple with iPhone, Maemo could become developers dream and a serious competitor to iPhone. However if Nokia keeps its bad habit of producing zoo of semi-decent not-quite-compatible devices, with introduction of a new just-little-different device every quarter, just to break whatever compatibility still remaining, Maemo, with all its openess will not have practical advantage over Android.
Switching to OpenCV 2.0 with VS2005
I’m using OpenCV for some tests, and for some reasons (freelance gigs and Symbian SDK) using MS Visual Studio. As new and shiny OpenCV 2.0 is out I decided to switch to it. As it happen, one absolutely have to read buried in the download section readme, before doing anything.
The thing is, OpenCV 2.0 doesn’t include lib files for VS. They have to be built by user.
So here is step by step retelling of readme:
1. Rename your old OpenCV installation to save it, just in case
2. Download and install OpenCV 2.0a
3. Download and install CMake
4. Reboot (or CMake wouldn’t work)
5. Go to C:\Program Files\CMake 2.6\bin and run cmake-gui.exe
6. In the “Where is the source code” field choose your new OpenCV directory (C:\OpenCV)
In “Where to build the binaries” choose directory for VS compiled OpneCV (C:\OpenCV\VS2005)
7. press Configure button and choose VS2005 (or whatever) as building enviroment
8. Press Generate and VS project will be generated in the C:\OpenCV\VS2005
9. Launch solution and build it. For debug build some projects require debug python libraries. As riseriyo pointed in comments if you have Python installed other than 2.6 that can cause problem.
10. Copy *.lib from C:\OpenCV\vs2005\lib\release (or debug) to C:\OpenCV\lib
Copy *.dll from C:\OpenCV\vs2005\bin\release to C:\OpenCV\bin
11. Now, reconfigure your application project. Include directories now “C:\OpenCV\include\opencv” instead of “C:\OpenCV\include
12. All libraries renamed from *.lib to *200.lib (cv.lib to cv200.lib) or *200d.lib for debug. Rename them, or change project settings.
PS if you need Python and still have a problem with cvpy:
From readme:
Known issues:
=============
1. Python 2.6 bindings for OpenCV are included within the package,
but not installed.
You can copy the subdirectory opencv/Python2.6/Lib/site-packages into
the respective directory of the Python installation.
Here is riseriyo explanation how he deal with python problem
PPS Comment by rise about vs2008 issue:
dll and manifest file version conflict in msvc 2008. the only way i was able to fix this was to completely uninstall msvc 2008 and then do a clean install w/o updating it with the sp1 packages.
see his blog and how he was troubleshooting (for days) the issue
That’s it. Project should compile now. If not you still have your old OpenCV installation
Fast Fourier Transform for P2P networking
Very unusual application of FFT in this arxiv paper. Butterfly diagrams for radix-n FFT allow building P2P network with maximum diversity, reliability and flexibility and minimum complexity.
Still checking Gauss-Newton
Though Levenberg-Marquardt works I’m still trying to save Gauss-Newton, especially as I’ve read paper saying that Gauss-Newton with dogleg trust-region works well for bundle adjustment. I’ll probably try direct substitution with Cholesky rank-1 update and constrained optimization.
Solution – free gauge
Looks like the problem was not the large Gauss-Newton residue. The problem was gauge fixing.
Most of bundle adjustment algorithms are not gauge invariant inherently (for details check Triggs “Bundle adjustment – a modern synthesis”, chapter 9 “Gauge Freedom”). Practically that means that method have one or more free parameters which could be chosen arbitrary (for example scale), but which influence solution in non-invariant way (or don’t influence solution if algorithm is gauge invariant). Gauge fixing is the choice of the values for that free parameters. There exist at least one gauge invariant bundle adjustment method (generalization of Levenberg-Marquardt with complete matrix correction instead of diagonal only correction) , but it is order of magnitude more computational expensive.
I’ve used fixing coordinate of one of the 3d points for gauge fixing. Because method is not gauge invariant solution depend on the choice of that fixed point. The problem occurs when the chosen point is “bad” – error in feature point detector for this point is so big that it contradict to the rest of the picture. Mismatching in the point correspondence can cause the same problem.
In my case, fixing coordinate of chosen point caused “accumulation” of residual error in that point. This is easy to explain – other points can decrease reprojection error both by moving/rotating camera and by shifting their coordinates, but fixed point can do it only by moving/rotating camera. It looks like if the point was “bad” from the start it can become even worse next iteration as the error accumulate – positive feedback look causing method become unstable. That’s of cause only my observations, I didn’t do any formal analysis.
The obvious solution is to redistribute residual error among all the points – that mean drop gauge fixing and use free gauge. Free gauge is causing arbitrary scaling of the result, but the result can be rescaled later. However there is the cost. Free gauge means matrix is singular – not invertible and Gauss-Newton method can not work. So I have to switch to less efficient and more computationally expensive Levenberg-Marquardt. For now it seems working.
PS Free gauge matrix is not singular, just not well-defined and has degenerate minimum. So constrained optimization still may works.
PPS Gauge Invariance is also important concept in physics and geometry.
PPPS While messing with Quasi-Newton – it seems there is an error in chapter 10.2 of “Numerical Optimization” by Nocedal&Wright. In the secant equation instead of 
