Today I played the game Ether Vapor again. This is the 4th time I've cleared this game! (>_<)b

The game was released at 12/31/2007. Wow, that's 3 years ago... The group are still working on their latest game however still no update since January. I like Ether Vapor very much. As a computer science student, I always want to implement something that can inspire myself and also make profit. Ether Vapor was come from an idea of the administrator of the group, Nal. He started working on the game since 2005. He spent early 3 years to finish that game and release it for only 1500JPY each!

I saw this game first time when I was a junior undergraduate student. I don't have time to build a game at that time, also I don't have the skills to do so... But I think I can actually start to create something that I'm interested in. People always say that doing what you want is actually a kind of happiness. That's true!

Therefore, I'm going to first work on some books about computer graphics and try to figure out which kind of technologies I'm going to use. For now, I can build 3D models through 3ds max and code games through XNA... But that's not enough. The aim is to build tomorrow games today!

Finally, I want to express my thankfulness to the staff of Ether Vapor. You guys did a great job! And you have inspired a programmer to brave enough to build a better world!

## Thursday, March 24, 2011

## Tuesday, March 22, 2011

### Project "3D point cloud classification"

The project names '3D point cloud classification'. I'm excited about 3D point cloud, and I thought the project should have something to do with the real-time 3D reconstruction...

The main purpose of this project is to help robotics and automated vehicles to recognize where is road and where they cannot go. The project itself is very practical, however it has a lot to do with mathematics -_-. From a software engineer point of view, this kind of project should have some kind of API exists. And, yes! We are going to use it without dive deep into the algorithm~!

However, theories and algorithms are part of the reason why I chose CS instead of SE as the graduate major. ^_^ Therefore, complains are allowed, but evasion is prohibited!

頑張ろ！

Now back to the algorithm...

We all know that 3D cameras and LIDAR sensors can only generate 3D point clouds. Point clouds cannot be used until classification or reconstruction. Reconstruction is a series of processes to convert the point cloud into 3D objects and models. Classification is light-weight compared to reconstruction. We only need to specify the type of objects formed by some points. In other words, we only need to recognize if there's a valid path (or plane) for robotics to pass.

1. For each point in the cloud, find all neighbors within a specific range.

2. Compute the weight point of those neighbors. Say the weight point is x-bar, we found N neighbor points and Xi is the matrix [x,y,z] contains dimensional information of the original point. The computation of x-bar is 1/N*Sum(Xi).

3. Compute the covariance matrix using the value of x-bar. The formula to compute the matrix S is 1/N*Sum((Xi-x_bar)(Xi-x_bar)T). The matrix is a 3X3 symmetric positive definite matrix.

4. We need to decompose the matrix and get the eigenvalues λ0, λ1 and λ2.

5. Say v0, v1 and v2 are the eigenvectors corresponding to eigenvalues λ1, λ2 and λ3 respectively. We build a support plane using v0, v1 and x_bar. Vector v2 is the normal of that plane and x_bar is the center of the plane.

6. We now compare the three eigenvalues. If λ0≈ λ1≈ λ2, it means those points are scattered in the space. If λ0>> λ1, λ2, it means those points spread in a linear pattern, for example in a cylinder. If λ0≈ λ1>> λ2, those points are likely to be on a surface.

So~ First of all, I need to figure out the CPU version of the code, which means the code must first work. And then, I'll try to port it to グラフィックカード and see if we can increase the performance.

The main purpose of this project is to help robotics and automated vehicles to recognize where is road and where they cannot go. The project itself is very practical, however it has a lot to do with mathematics -_-. From a software engineer point of view, this kind of project should have some kind of API exists. And, yes! We are going to use it without dive deep into the algorithm~!

However, theories and algorithms are part of the reason why I chose CS instead of SE as the graduate major. ^_^ Therefore, complains are allowed, but evasion is prohibited!

頑張ろ！

Now back to the algorithm...

We all know that 3D cameras and LIDAR sensors can only generate 3D point clouds. Point clouds cannot be used until classification or reconstruction. Reconstruction is a series of processes to convert the point cloud into 3D objects and models. Classification is light-weight compared to reconstruction. We only need to specify the type of objects formed by some points. In other words, we only need to recognize if there's a valid path (or plane) for robotics to pass.

**To do the job, we need several steps:**1. For each point in the cloud, find all neighbors within a specific range.

2. Compute the weight point of those neighbors. Say the weight point is x-bar, we found N neighbor points and Xi is the matrix [x,y,z] contains dimensional information of the original point. The computation of x-bar is 1/N*Sum(Xi).

### First post

Hello me!

I've moved to blogger now since I don't think wordpress is easy enough for me to use... and Microsoft shut my share-space down (although there's nothing important inside).

From now on, I will try to write blog posts as often as possible. Sometimes I really want to post some of my work and programs online, I'll try to do that now!

I'll put assignments, projects, news, programs and drafts here. Hope those materials can help me in the future!

I'm confident that I can keep on writing this time~

See you in the future~!

I've moved to blogger now since I don't think wordpress is easy enough for me to use... and Microsoft shut my share-space down (although there's nothing important inside).

From now on, I will try to write blog posts as often as possible. Sometimes I really want to post some of my work and programs online, I'll try to do that now!

I'll put assignments, projects, news, programs and drafts here. Hope those materials can help me in the future!

I'm confident that I can keep on writing this time~

See you in the future~!

Subscribe to:
Posts (Atom)