http://blog.sina.com.cn/s/blog_4c3782760100gp2p.html

对整个中国社会已经彻底失望了。

好多年没有做总结了，只是觉得如果随时都在思考，那么抽出一段时期中的某个时间点来进行特殊的思考发散就不是特别必要了。然而这一年实在是读书有限，特别是开始学习了之后，发现虽然天天都在读别人的工作，而认真想书里内容，温习的时间真是太少太少了，以至于身旁全是书签夹在一半处的林林种种。近两年来，学术实无精进，只是徒增技能和所谓见识，以至于对现状更加失望罢了。

首先的失望，来自于对中国情况的更加认识。在几年前曾经会幼稚地认为中共的高层仍然是具有智慧和见识的，然而这几年的亲历让我觉得，中国自然是有不乏具有智慧和见识的人士，但是很可惜却不是中共政治局中的那一干人等。正是由于这点的认识和对中国人口年龄分布的担忧，使得对于这个国家的前途更感觉不祥。尽早的布局便是既维持在中国的联系，也加强在美国的联系和途径。

其次的失望是对大多数人探索欲望的失望。尽管仍然有大量的人对太空充满热情，但是步伐仍然太慢太慢了。而且由于人权意识的开化和人身价值的加强，商业太空发展将会面临很大的阻力，归根结底，太空探索会死人，而且会死不少的人。如果像航天飞机一样出一次事故就停飞几年，步履也太蹒跚了。

但是，总会在失望中隐含着希冀，会有斗争让国家更好；而太空在那，我们一定会到达。

Since 2005, most of my computer vision work were done with OpenCV. It is an amazingly hand-optimized piece of software. A large number of modern applications are based on OpenCV framework. It is a useful toolset. However, for all this years, I finally feel the need to make a more lightweight, pure-c/function based library. There are some ideas:

1. It should be fast. There is no need to build a toolset that is slow. Former work such as lapack and gsl are a better choices rather than reinvent the wheel. For the same reason, It is necessary to fork basic routines from OpenCV, such as Canny detector, kalman filter, etc.

2. Better memory management, cache everything. OpenCV partially implemented a memory management routine, but failed to have a cache mechanism, partly because there are too many functions and it hard to break in and add another layer.

3. Less but more about modern algorithms. Implementing a fewer but niche algorithms and give intuitive examples. Keep compatibility with OpenCV (through interpreting functions).

4. Give some love to distributed system, and modern compilers (LLVM & Clang).

I am aware of that many vision works are never made the way to mass (VLFeat for example), but that’s the plan.

but time is too short.