Showing posts with label Russia. Show all posts
Showing posts with label Russia. Show all posts

Kinect Apps Challenge

Posted in Labels: , , , , , | at 20:54

Graphics & Media Lab and Microsoft Research Cambridge have announced a contest for applications that use Kinect sensor. The authors of the five brightest apps will be funded to attend the 2012 Microsoft Research PhD summer school. I blogged about the last year's event in my previous post. Details of the contest are here.

I guess there's no need to explain what Kinect is. It is extremely successful combined colour and depth sensor by Microsoft. It is being distributed for killer price (≈$150) as an add-on for Xbox, although it is hard to imagine the range of possible applications. Controlling a computer only by gestures is considered as a primer of natural user interface. To name some applications beyond gaming, this kind of NUI is useful to help surgeons to keep their hands clean:

Kinect helps blind people to navigate through buildings:

For more ideas look at the winners of OpenNI challenge.

OpenNI is an open-source alternative to Kinect SDK. Its strong point is it is integrated with PCL, but beware that you cannot use it for the contest. Only Kinect for Windows SDK is allowed.

Kinect is probably the most successful commercial outcome from the Microsoft Research lab. MSR is unique because they do a lot of theoretical research there, and it is unclear if it is profitable for Microsoft to fund it. But the projects like Kinect reveal the doubts. I will post about MSR organization in comparison to other industrial labs in one of the later posts.

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[CFP] GraphiCon-2011 and MSCVSS

Posted in Labels: , , , , , , , , , | at 00:36

Our lab traditionally organizes GraphiCon, the major (and may be the only) conference in Russia specialized in computer graphics and computer vision. The conference is not very selective, still it has a decent community of professionals behind it. So, if you want to get a quality feedback on your preliminary work, or always wanted to visit Russia, consider submitting a paper by May, 16.

Special offer for young readers of my blog: If it is the place where you learned about the conference and decided to submit a paper, I'll buy you a beer during the conference. :) Consider it another social micro-event.

Another piece of news is primarily for undergrads and PhD students from Russia. Our lab and Microsoft Research organize another event this summer: Computer vision summer school. There are such lecturers as Cristoph Lampert and Andrew Zisserman, among others. Participation is free of charge, and accommodation is provided. Deadline is on April, 30. You should not miss it!

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The one about CERN

Posted in Labels: , , , , | at 23:02

About a month ago I visited CERN, arguably the most famous research organization in Europe. It is the place where the World Wide Web has been invented, and the home of the Large Hadron Collider. I was very excited about the trip, much like Sheldon Cooper. Here are some facts which were new to me:

... about CERN:
  • CERN was founded after the WWII by a bunch of European countries. They were exhausted by the war, and the only way to catch up with the USA and USSR in fundamental science was to join forces.
  • The original name was Conseil Européen pour la Recherche Nucléaire (European Council for Nuclear Research), which abbreviated to CERN. Later the name has been officially changed to European laboratory for particle physics, which is both more relevant and less fearful for the locals, however the brand CERN is used now even in official documents.
  • There are almost 3,000 full-time employees, but most of them are engineers and not scientists. There are a lot of visiting researchers though.
  • There are 20 member states now (primarily EU states), and 6 observer states (such as Russia and the USA).
  • CERN's annual budget is about € 1 billion, it is funded by the member states in proportion to their economical power, e.g. Germany gives 20% of the money.
  • The budget money are spent to infrastructure and support, all the individual experiments are funded by research groups and their universities.
  • In spite of the USA is not a member state, it leads on the number of researchers who work on CERN projects (more than thousand), second is Germany, third is Russia (yes, we still have a good shape in particle physics). It turned out that everybody at CERN spoke Russian, even the janitor. :)

... about the LHC:
  • It is in fact a circular tunnel of 27 km in circumference lying 175 m beneath the ground.
  • The tunnel was used before the LHC, it was build in 1983 for the Large Electron-Positron Collider. In 2008 it was upgraded to be able to accelerate heavy particles like protons to become the Large Hadron Collider (remind that proton and neutron are thousand times heavier than electron).
  • The tunnel is about 4 meters in diameter, one can walk there or ride a bike.
  • The tunnel encapsulates two small pipes for the particles that intersect at four points (to make the tracks' lengths equal, like in speed scating arenas). There are more then a thousand of electric magnet dipoles along the pipe. They are not that big as I imagined before.
  • It is nearly vacuum and zero temperature inside the tubes.
  • Proton beams are not generated inside the LHC. First, they are accelerated in the linear accelerator and almost reach the speed of light c. While the speed is rising, it becomes harder and harder to increase it since it cannot overcome the speed of light. Then they are accelerated in the small circular accelerator, and only after that they are injected into the LHC where during 40 minutes the beams are accelerated to speed as much close to c as possible.
  • When accelerated, the beams are being observed during 10 hours. They suffer about 10,000 collisions per second, about 20 pairs of protons collide each time. Since the speed is large, the energy of that collisions is enormous.
  • The collisions take place within special locations called detectors. We visited a control centre of one of them, ATLAS. A detector has multiple layers, each able to register certain kind of particles, like photons.
  • Ten thousand collision per second would yield really big amount of data, so only few of them are selected to be logged. I don't know how they select those collisions, machine learning might be used. :)
  • All the collected data are spread into servers all over the world. An authorized researcher may log in to the grid network and execute her script to analyse the data.
... about Higgs boson:
  • Higgs boson is a hypothetical particle, existence of which would prove the standard model of particle physics.
  • Higgs boson appears as a result of collision of two protons and large amount of energy. The protons in the LHC are accelerated enough to produce theoretically sufficient energy.
  • Higgs boson is very heavy and thus unstable. In theory, it decays into either four muons or two photons. So, if there will be two counter-directed light beams registered by the detector, this will be an evidence of the boson. See the picture below for example of likely detector output in case of the boson shows up.
  • Scientist say that if Higgs boson would not be detected, all the modern knowledge on particle physics will crush. They will be obliged to develop a new theory from scratch.
  • There are no published results that report on Higgs boson detection so far...


Don't you want to be a theoretical physicist now? =)

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ICVSS 2010: Have you cited Lagrange?

Posted in Labels: , , , , , , , , , | at 20:33

Yeah, I have. :) Before the beginning of the summer school we received a homework assignment from Prof. Stefano Soatto. We had to read the three papers and discover the roots of ideas exploited by the authors. Such connections are not obligatory expressed by references. As a result, one had to get a tree (or, may be, lattice) with a root in the given paper. Since the task was not accurately formulated, most of us chose just one paper and made a tree for it. Later it turned out that all three problems (optical flow estimation, multi-view stereo and volume registration) have the same roots because they lead to the similar optimization problems and we were supposed to establish that connection.

I (like most of the students) had a limited time to prepare the work. All the modern research in optical flow is based on two seminal papers by MIT's Horn & Shunk and CMU's Lukas & Kanade, both from 1981. During the last 30 years a lot of work has been done. It was summarized by Sun et al. (2010), who discovered that only small fraction of the ideas give significant improvement and combined them into quite simple method that found its place on the top of Middlebury table. Since I had no time to read a lot of optical flow papers, I discovered a lot of math stuff (like PDEs and variation calculus) used in Horn-Shunk paper. Just as a joke I added references to the works of Newton, Lagrange and d'Alambert to my report. Surprisingly, joke was not really understood.

There were only 21 submissions, one of them was 120 pages long (the author did not show up at the seminar =), the tree depth varied from 1 to 20. I was not the only one who cited "pre-historic" papers, someone traced ideas back to Aristotle through Occam. The questions about the horizon arose: it is really ridiculous to find the roots of computer vision at Aristotle works. Since the prizes were promised for rare references (the prize policy was left unclear too), some argument took place. Soatto did not give any additional explanations on the formulation of the task but let the audience decide which references are legitimate in controversial cases. Eventually, I was among the 5 people whose references were considered controversial, so I needed to defend them. Well, I suppose I looked pretty pathetic talking about Newton's finite differences which were used for approximation of derivatives in the Horn-Shunk's paper. Surprisingly, almost a half of the audience voted for me. =) Also, my reference to the Thomas Reid's essay was tentatively approved.

Finally, there were no bonuses for the papers that could not be found with Google, and the whole $1000 prize went to the Cambridge group. To conclude, Soatto (among other) said that nobody had read any German or Russian papers. After the seminar I told him how I tried to dig into the library (it is described here in Russian), he answered something like "funny, it is hard to find them even for you!"

One evening during the dinner we talked about Russia, and Vijay told a lot of interesting stuff (like the guy who developed ChatRoulette is now working in Silicon Valley). He remembered Stephen Boyd who is known for his jokes about Russia. I said that I watched the records of his amazing course on Convex Optimization. It turned out that Vijay (who is now a PhD student in Stanford) took that course, and he promised to tell Boyd that he has a fan in Russia. (Or, maybe in Soviet Russia fans have Boyd =).

continued here

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ICVSS 2010: lectures and posters

Posted in Labels: , , , , , , , , , , | at 03:17

I returned from my eurotrip yesterday and now I am ready to start a series of posts about International Computer Vision Summer School (ICVSS 2010). Generally, I enjoyed the school. That week gave me (I hope) a lot of new knowledge and new friends.

The scientific programme of the school included lectures, tutorials, a student poster session and a reading group. Lectures occupied most of official programme time and were given by a great team of professors including Richard Szeliski, renowned Tomasso Poggio and enchanting Kristen Grauman. I am not going to describe all the talks, but feature the ones that are close to my interests. You can find the complete programme here. Unfortunately, no video was recorded, but I have an access to all the slides and posters, so if you are interested in anything, I can send it to you (I believe it does not violate any copyrights).

Wednesday was the day of Recognition. Kristen Grauman gave a talk about visual search. She covered the topics concerning specific object search using local descriptors and bags of words, object category search with pyramid matching, and also discussed state-of-the-art in the challenging problem of web-scale image retrieval. Mark Everingham continued with a talk about category recognition and localization using machine learning techniques. Localization is reached using bounding boxes, segments, or object parts search (like finding eyes and a mouth to find a face). Sure he could not avoid to mention importance of context. He also explained the PASCAL VOC evaluation protocol.

The tutorials covered some applications and did not really impress me. Poster session was a great opportunity to meet people. Some posters were really decent, for example Michael Bleyer's poster on dense stereo estimation using soft segmentation, which won a half of the school's best presentation prize. The work was done with Microsoft Research Cambridge, they formulated a really complicated energy function based on surface plane estimations and minimized it with Lempitsky's graph-cut based fusion-move algorithm (2009). More details could be found in their recent CVPR paper.

The problem with the poster session was that lecturers did not attend it, although they could really give a great feedback. My presentation was in the last day of the session after the not-really-popular reading group and in the room upstairs (its existence was not a well-known fact :), so many people preferred to spend that evening on the beach. The school audience was quite heterogeneous, there were a lot of people from medical imaging, video compression etc., so I had to explain some basics (like MRFs) to some students interested in my poster. There were also really smart guys (like those from Cambridge group). There was a bit of useful feedback: someone recommended me to use QPBO for inference, and I should probably consider it.

Since the speakers did not attend the poster session, students had to communicate with them informally. A roommate of mine, Ramin, who does a crowd analysis, caught Richard Szeliski and asked him about local descriptors in video that operate in 3D image-time space. Szeliski told that it is a promising field and even remembered Ivan Laptev's name. During our tour to Ragusa Ibla I asked Mark Everingham (who is probably the closest of all speakers to my topic) about 3D point cloud classification. He said it was not really his field, but it should be fruitful to analyse clouds not only in local levels, and stuff like multi-layer CRFs could be useful. During the last 2 years there appeared a few papers that exploit that simple intuitive idea and incorporate shape detectors with CRFs, but it usually looks awkward. Well, may be smartly designed multi-layer CRFs might be really useful. It is funny, when I told Everingham that I'm from Moscow he replied that it was great, Moscow has a great math school and remembered Vladimir Kolmogorov. So, our education seems to be not so terrible. :D

continued here

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ICVSS 2010

Posted in Labels: , , , , , , | at 22:16

This summer I'm going to take part at the International Computer Vision Summer School. I have already been accepted and registered for it. I'm really looking forward this event and hope it will not be too hot in July in Sicily. =)

I am now seeking for a room-mate, because accommodation is quite expensive there. If you are a participant too and have a similar problem, please feel free to contact me!

One of the activities of the school is a reading group leaded by Prof. Stefano Soatto. As a homework, we need to investigate the reference trees on three certain subjects. Moreover, there will be prizes for students who will have discovered papers that could not be found via standard search engines. I suppose I have a bonus here: Russian science has been isolated from the, well, science due to that iron curtain thing (it is still quite isolated, by inertia). So, I just need to dig in a library and find something appropriate in old Soviet journals.

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University education reform

Posted in Labels: , , , | at 23:20

Recently, me and my friend Andrew Korolev came up with the plan of reforming Russian higher education system.


There are some evident problems in the system one can notice even in our faculty. The most courses are obsolete (or, well, legacy), a lot of courses are not enough developed (e.g. they contain only lectures without any support), some of them are also over-theorized and not applicable in real world (or at least they don't touch upon their applications). As a result, students are not motivated, they don't attend lectures and learn everything during the two-day period prior to the exam. The grades are often lousy, but nobody cares since such grades are sufficient to continue studying. (It is difficult to fail totally, especially for non-freshmen). Such knowledge is not solid and quite useless.

We make use of the following facts. The professors are well-qualified here, the students are witty and communicate with each other and with the graduates. Also, we suppose that everyone wants get more money, which is not always hold though is pretty common.

First, we need to improve the quality of courses. The problem is how to measure the quality. We state that it is proportional to the number of students who choose the course. Since the students have enough information about the course (from the lecturers and other students) and they all want to make a magnificent career, the useful courses become popular. The professors should be paid according to the number of students who attend their courses. But students also want to save their time. So, they are likely to choose the least challenging courses, which are not useful. In order to penalize them, the course part of professor's salary should be eliminated by the fraction of positive grades students get. Thus, a professor is motivated to make a comprehensive course (to attract students) and to implement a severe grade policy (to eliminate the freebie).

However, it will never work if the students are not motivated to get the good grades. In Russia, we have 4-level grades (2 through 5; 3 is enough for the pass), and most of the students are happy with 3s. Today, there are two stimuli to get greater grades, but they are quite subtle. The first is one need almost all 5s to receive the degree with honours, but who needs that? The second is 20% increment to the scholarship, which amounts not as much as one can desire. I have all excellent grades and receive some personal Sberbank scholarship, and totally it is about €100 per month. So, this is not a stimulus.

Well, one can ask, why do the students study now, if the courses are far from perfect? The answer is the conscription. In Russia, while you keep studying, you have a delay. If you fail at an exam, you get expelled and go to the army. Obviously, nobody wants to go to the Russian Army. So, everybody can learn a bit to pass an exam. Our point is to motivate students this way: if you have lousy grades, instead of summer holidays you move to a military camp. Better grades you get, less term you should serve. Thus, students WILL get good grades! But it is hard to get them, because professors loose their money. It is kind of a dual problem.

Surely, the model is way rough and could not be applied directly. Moreover, it is too funny to be taken seriously, though, as Russian proverb says, every joke contains a bit of truth.

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The disruption of scholarly publishing [in Russia]

Posted in Labels: , , , , , , | at 10:39

You know, I am relatively new to the big science. The first 2-column paper I read was Antonin Guttman's paper about R-Trees.1 It was about 2.5 years ago. So, I've never used published journals or conference proceedings. I have been wondering why do they spend money to printing journals if the researchers usually publish their papers on their home pages. Recently, I've read the article about the disruption of scholarly publishing by Michael Clarke. The article is quite dragged out, so I summarize its ideas in the following paragraphs.

When Tim Berners-Lee came up with the idea of WWW in 1991, he thought of its purpose as some kind of scientific media, which would replace conferences and journals. Nowadays, the Internet is used for social networking, illegal distribution of music and pornography, but we still have journals and conferences off-line. Why?

The author indicates 5 main points:
  • Dissemination - journals distribute papers all over the world
  • Registration of discovery - to know who was the first, Popov or Marconi
  • Validation - to ensure that the results are correct; now provided by peer-review
  • Filtration - you are likely to read a paper from the journal with bigger impact factor
  • Designation - if you have publications on top conferences, you might be a cool scientist
The author argues that only the last point is critical for the modern system of journals and conferences. The others could be better handled with on-line services, we already have a lot of examples.

But in Russia, we don't rank scientists according to their citation index!2 (because we don't have one :) ) So, the designation problem is not solved here, and Russia is already ready to the new publishing system. Why do we still have journals? I don't know, probably the sluggishness of minds...

1 Actually, I had read this paper about Google before, but it accidentally was not 2-column formatted. :)
2 I am cunning a bit: some journals carry out designation purposes. I mean journals published by VAK. One should have at least one publication in such a journal to get Candidate of Science degree (Russian PhD equivalent). But the review process is usually lousy, there was also Rooter case with one of them.

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