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致有意加入計算機圖學實驗室的研究所新生

首先恭喜你錄取本系研究所,如果計算機圖學的各項研究令你驚奇,而想進一步探究作為你的研究方向,那麼十分歡迎你加入計算機圖學實驗室,但請先注意以下幾點:

  1. 每年我會收到許多剛考上研究所的準新生來信,想約時間詢問我的研究領域,今年我對這類型的來信將一概不回(連我的領域是甚麼都不知道,還來找我做甚麼?),如果你已經看到這裏,相信你不會有這個困擾了。
  2. 我們實驗室的研究主題,大多環繞三維計算機圖學的繪圖技術與演算法,而不在內容的美工設計或創作,若以電腦遊戲或動畫為例,我們將著重在繪圖引擎的開發,而非遊戲或動畫的內容。
  3. 也因為上述,程式設計是不可或缺的能力,我們將大量使用C/C++和OpenGL。你不必學過C/C++和OpenGL,但需至少有其他程式設計的經驗。
  4. 三維圖學計算需要大量的運算資源,因此我們也會接觸各類有效率運用繪圖處理器(GPU)和多核心處理器的相關平台或技術,例如GLSL與OpenCL。
  5. 若你讀到這裡,覺得計算機圖學適合你,那歡迎來找我一談,但請前來我研究室之前,先email給我,因為我有許多時間不在研究室,不希望你白跑一趟(而且要爬樓梯到五樓)。
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i++ (和自己賽跑的人)

給師大資工(或曾念過本系)今年的畢業生:

不要覺得自己是魯蛇(loser)
很多時候一時win or lose沒那麼重要
重要的是像C語言的 i++ 一樣
下個clock cycle的 i 超越現在的 i
明天的我超越現在的我
現在覺得渺小,就不會overflow志得意滿

最後播放一首,前天金曲獎的得主李宗盛,在我大學畢業那年的作品:
和自己賽跑的人

笨蛋,問題不在排序!

剛做了一個夢,大家開始不管十二年國教的排序公不公平,而開始討論怎麼讓有熱情的流浪教師進入需要他們的高中,以及如何讓現任的老師在政策一再轉彎下僅剩的熱情能重新點燃,從此每個高中都是明星高中。

不過夢畢竟只是夢,而我不是Martin Luther King

夏天在紐奧良Preservation Hall聽Jazz

DSC00489

剛從New Orleans參加SIGGRAPH 2009回來。 今年六月到紐約,八月到紐奧良,各看了一場世界聞名的現場表演,在紐約Majestic Theatre的The Phantom of the Opera和紐奧良Preservation Hall的Jazz。

這兩個表演存在著很微妙的對比。先從客觀數字講起好了,在紐約的Phantom票價將近一百美元,台上的演出者大概有將近百位吧,從我座位到舞台的距離也大概是數十公尺。在紐奧良Preservation Hall的Jazz就大概是把上面的數字都除以十。 是的沒錯,在Preservation Hall我和演出者距離就是那麼近,如果可以跨過前面比我更近的兩三排觀眾,只要走兩三步我就可以和演出者(有些應該是國寶級的)握到手了。

在Preservation Hall的經歷很特別,在這邊名氣不會轉變成演出者和觀眾之間的距離,包括有形和無形的距離,一切都保留在那個遙遠年代的氣氛中。在美國南方燥熱的夏夜裡,即使小小十坪左右的空間裏擠了幾十個人,演出者也不停的擦著汗,Preservation Hall裏依然只開著電風扇,沒有冷氣,像是清清楚楚的傳達這個訊息,要吹冷氣就買CD回去家裡聽,要聽現場就和大家一起流汗。

Why should Mozart be a full professor and Beethoven an assistant professor?

According to the SCI (Symphony Composer Index), Beethoven has 9 published SCI-indexed works while Mozart has more than 50 SCI-indexed works.

OK, just kidding, I made those up.

Still, similar arguments and fallacy often pop up in Taiwan’s academia.

Nathalie’s first bicycle ride

It may be a father’s dream to catch his baby’s first step, that definitive moment, on a video.  But if you’ve ever tried, you know how hard it is.  The lone success I have ever seen is in the “Truman’s Show” movie.

Yet, the opportunity presented itself again on July 20, 2008, when I realized that Nathalie was close to riding a bike completely on her own.  This time, I caught it on the DV tape.  Check this out.

Convolution and Multiplication

When I first learned Fourier Transformation in signal processing, I was told that the convolution of two signals in time domain (or spatial domain) was equivalent to the multiplication of those two signals in frequency domain.  That was amazing, but I got no intuition about why it worked.

Then one day, it hit me that I had been doing convolution since I was a kid in elementary school.  Every time we multiply two decimal numbers, we are not really performing the multiplication.  We are actually computing the convolution of their digits.  For example, the reason why we know 22*33 is 726 is because we compute the convolution of the two signals (2,2) and (3,3), which gives us the signal (6, 2, 7).  (Note: I put the least significant digit to the left, so they look more like the signal in the “transformed” domain.)

Still didn’t get it?  Then think about this.  What is the meaning of the decimal number system that we have taken for granted?  Imagine the world 5,000 years ago.  How would a farmer count the number of plants in his land?  For example, if he has 22 rows of plants, and 33 plants in each row, how does he count the total number of plants?  Does he know the total is simply 22*33 if he doesn’t yet know the multiplication of two decimal numbers?

  • 22 and 33 are the results of projection to the tens and the singles digits of the decimal system.
  • 726 is the result of the convolution between (2,2) and (3,3).