And then is the details of the exams themselves, which are worthwhile to applaud for. The forms of the exams are mostly based on the professors’ interests in three types: written exam, oral exam and others. Until now I have just take part in two exams, which are all written exam with decided date. As those two exams are from the same department of our TUB, the total points are the same – 33 Points. The questions cover almost all the topics in the lesson but in the form of some new applications, which make the works not so boring as some exams I took part in. But I have to admit that it is no so easy to get all the points while you must consider both the main frame of the topic and some details of the application in the limited time (90 min.).

A interesting situation is that I’m the only student in one course, so basically it is real one-one course and even the exams. And I’ll take it as oral exam, which will be my first experience in this form of exam in science’s topic. Neutrally I am from a few days before a bit nervous about this, but as the exam are more considering the application of the wavelet technology, which takes a long time in first part of the course and I think I have already got the main idea and basic details. And the reason I choose this course is on the application things and the passed experiences of one of my not so good project is also on this fields. (go on) Finally I took the exam of this course with a two hour long oral exam, which takes usually only 30 minutes. But I have to commit that the exam is more like a additional lessen rather than a exam itself, the teacher give me a lot of different views that I don’t even think in that direction, such like how can people make the derivation of Zero-tree Methods using wavelet transform.

I have still two oral exams in this semester and one more written exam in the end of next semester. So, just fighting!

Task 1: Chinese Support

After searching through the google, I finally select a solution: A software named FontRouter with the use of some Unicode Fonts.

FontRouter is some Font Driver Software, the homepage of this project is http://code.google.com/p/fontrouter/ , on which the certain version can be found (Nokia E71 use S60 3rd. system, so choose the version for Symbian 6). By the way, the downloaded software may need to be signed before the installation on mobile, since it is really common situation for Nokia user, I don’t think it is difficult and many solution for this can be easily found on internet. The Unicode Fonts can be selected totally based on your favor, and what you have to do is only to download it and save it in the special folder for FontRounter in Mobile.

Restart the mobile and Chinese is available, of course with the UTF-8 coding, which is also common, at least I get no trouble with email and google reader.

Task 2: Softwares

As my mostly interests on mobile focus on the application with internet and reading, so I pick a list of the softwares I used in my E71:

S01. fring : A famous IM software on mobile, which can use the accounts of Skype, MSN, Twitter and so on at the same time. For me its task is using voice call with skype using 3G or  wifi. You can download it from http://www.fring.com/

S02. Mail for exchange : A software from Nokia website, which can make the connection between mobile and exchange server. I use it to connect to google service to sync my contact list and calendar. You can find it on nokia’s site.

S03. Google Mobile ：A set of google tools, from which I can easily use Gmail, Google Maps and Google Reader. You can download it from  http://www.google.com/mobile/

S04. twittai ：A Twitter client software, which have almost all the basic function of twitter and well support for Chinese. You can download it from http://www.twittai.com/

S05. Baidu Input ：A chinese input software from Baidu, You can download it from http://ishouji.baidu.com/input/

S06. Youdao Dictionary on mobile ：A mobile dictionary from Neteast, which have the abilities for online searching and words acquisition from camera. You can download it from http://m.youdao.com/help/cidian

Here is output of the 5th. homework.

Figure 1.

Figure 2.

The main task is to do both Projective Reconstruction and Euclidean Reconstruction given corresponding point pairs and some control points in euclidean coordinates.

In Projective Reconstruction we firstly calculate the fundamental matrix from the given point pairs and then derivate the projective matrices using normalized configuration (the most simple way) . With all this information a linear triangulation method is used to calculate the corresponding object points in projective space. And those procedure is so called Projective Reconstruction (of course the simple without any optimization).

In Euclidean Reconstruction we simply using all the information we got from the Projective Reconstruction and make the same procedure to the control points. At the mean time we calculate the spatial homograph using the control points.   Finally all the object points in projective space are transposed into euclidean space using the same spatial homograph, and that is so called Euclidean Reconstruction (without any optimization).

My document(PDF format) of this homework is below, if you have interest, maybe you can read it.

Homework 5. of Photogrammetric Computer Vision – 3D Reconstruction

Figure 1.

Figure 2.

Figure 3.

The task of figure 1. is to identify the origin shape after some scaling, moving, rotating operations with the help of so called Hough Transform. The task of figure 2. is a advanced version of the task before, which will identify the money from a complicated scene. The task of figure 3. is mostly used in camera calibration to automatically find out the control points, which then can be used to calculate the calibration matrix and the parameters of camera.

My document(PDF format) of this task is below, if you have interest, maybe you can read it.

Homework 2. of Automatic Image Analysis – Hough Transform

Figure 1.

The two images in the left show two type of leaves that we want to identify in the right-up image, and the right-down image is the result of my algorithm.

The algorithm just need a so called Fourier Descriptor to finish the job and actually some morphology operators to find out the edges of each leaf.

My document(PDF format) of this task is below, if you have interest, maybe you can read it.

Homework 1. of Automatic Image Analysis – Fourier Descriptor