Chess Tutorial Using Google Glass and Structure Sensor


Chess is a globally recognizable game originated in India that is played with two players. The game is consisting of 16 pieces for each player; player can win whether by opponent resign or capture the opponent’s king. Chess is a very competitive game that has many tournaments happening across the world. In recent years, more and more advanced chess computer algorithms (AI) have become available. One of the most famous one is the Deep Blue. In 1997 IBM computer Deep Blue take on human chess champion Garry Kasparov, and it is the first time for machines to overtake chess champion. Nowadays more and more chess machines are used to detect cheating in chess tournaments. Why is chess so important? Why are there so many children nowadays that are interested in playing chess? People commonly believe that chess and IQ are positively correlated, however, research has found that there are indeed no correlation between the general intelligence and their success in chess( In my DH project, I co-operate google glass and iPad structure sensor to produce an internet friendly chess tutorial on one of the classic chess opening for white, the stonewall attack. Traditionally, chess is taught by teachers, face to face. Nowadays, by adapting technology, more and more things can use internet as a platform to access to more people, including the chess tutorial my project is on.




Use google glass to have the first person perspective of a chess opening, use structure sensor to have the 3D structure of the chess board.

In the google glass record, I will at first go through the introduction of stonewall attack pawn structure, and the traditional pieces moving order that lead to stonewall attack, and then go through some variation of the opening. At the end I will go over a sample game that is being played. With first person perspective, audience can see the chess board as if they are in front of the chess board. With my detail explanation of why certain moves are made, it can help my audiences improve on their general chess skills.

Structure sensor can also be used to improve understanding of the spatial dimension of the game situation, which helps to improve understanding of how the opponent’s point of view and how your opponent counters your move. How to go about making it? After making a chess model using iPad structure sensor, I will out file the model onto my computer. As the model already captured the entire board, classify pieces based on its physical features and place a marker to each chess piece. In this way we can distinguish different pieces with different rules based on how they move, and have the fully understanding of what the game situation is like.

To co-operate both tools, every time a new move is made on google glass, a new chess 3D structure is also produced. Audiences can rotate around the chess board model to inspect on different angles, which helps the audiences to understand the game situation.



What has been done?

I successfully recorded Stonewall Attack chess opening video using google glass, and by utilizing the internet, I uploaded the video from my pc to youtube platform. Along with the video, I successfully used the scanner on the iPad to make a 3D model of the chess board and the initial condition of the chess. The video tutorial went through the basic concepts of what a stone wall attack is, the basic variations of the opening and a standard game scenario of the stonewall attack.


3D Structure:



The first person recording function is difficult to produce stationary video. When I start recording the tutorial, I will have to think about what move goes next. I always unconsciously swing my head which produced shaky first person video and it is hard to avoid even when I repeated recorded myself for many times. This made it hard to see the chess board in the video. The structure sensor model also has low resolution and limited detail, which will make it hard to actually classify chess pieces based on its geometry, when I uploaded my model to sketchfab, it also failed to convert the texture file of my chess. The first person perspective of the chess tutorial is also not very helpful; a digital chess board can do a much better job.

Future research

Co-operate the video recorded using google glass and the model of structure sensor. Ex: potentially, every time I made a move on my google glass, structure sensor captures the new move I made, and the model from the structure sensor can be used to see how that specific move looks for any angle you choose.

Write computer codes to supplement the model built from the structure sensor, to identify all the squares that your pieces is taking control over, use darker color for the more control you get over your opponent. Why is this important? When swapping pieces, the winner of the swap gain advantages by having more control over one single square. In general, visualizing the region of control is very useful. By investing into this function, it will be a lot harder for people to make mistakes on swapping pieces, and make my google glass video explanation easier to understand.

Utilize Virtual Reality with the model from the structure sensor, As the structure sensor model already have all the geometry information of the model, it wouldn’t be difficult to visualize chess pieces in front of you by adjusting the location of projection. By having this, it will drag more interests to children in getting into the sport.

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