Change Firefox Default Search Engine

1. Type about:config in Firefox address bar
2. Search for keyword.URL
3. Change the URL to any search engine you want
like the following
data:text/plain,keyword.URL=http://www.google.com/search?hl=zh-TW&source=hp&q=

The plugin list of VIM

It's time to organize my VIM plugins

My VIM Plugin Lists

1. SnipMate – provide TextMate like snippet. Use neocomplcache instead
2. SuperTab – use tab to complete words or sentence  Use neocomplcache instead    Can be configured to use tab key to trigger the snippet and word complete at the same time. Very cool~~~
3. FuzzyFinder – find files and functions in an instant 
4. L9 – required for new version of FuzzyFinder
5. EnhancedCommentify– comment and uncomment a piece of codes with single keystroke
6. DoxygenToolkit – generate function comment
7. a.vim – switch between .cpp and .h files
8. visual_studio.vim – compile VS files in VIM Not compatible with VS2010, 
9. omnicppcomplete – complete c++ files Use neocomplcache instead
10. surround.vim – make hello_world to "hello_world" with few key strokes
11. repeat.vim – make "surround" operation repeatable(with ".")
12. vim-latex – latex syntax support
13. matlab_run.vim – run matlab script in vim
14. matlab plugin for vim – provide syntax highlighting and indention of matlab
15. tlib – provides utilities for viki Use AsciiDoc instead
16. viki – support viki ( a kind of wiki language ) Use AsciiDoc instead
17. neocomplcache – it has been actively developed during recent months. It's mature enough.   It's interesting to see the author reply every blog which has questions about this plugin. It seems that the author really cares about his work.
18. neocomplcache-snippets-complete – since neocomplcache V7, the snippets have been separated from neocomplcache. You need to download it individually. 
19. delimitMate – parenthesis completion, very handy
20. cscope_map – provide keyboard mapping for cscope

Required Software:

1. Deplate – convert viki to html
2. Python 2.4.4 – required by Visual_Studio.vim
3. Ruby 1.86 – required by Deplate
4. ctags – required for omni-complete 
5. cscope 15.7 – a better ctags for python. The zip file contains windows binary.
6. Python for Windows Extension – required by Visual_Studio.vim

Abandoned plugins:

1. taglist – use FuzzyFinder instead
2. project – use FuzzyFinder instead
3. RltvNmbr – too slow included in VIM 7.3
   
4. snippetsEmu – too old, use SnipMate instead
5. neocomplcache – too new. It is a combination of omnicppcomplete, SnipMate, AutoComplPop and SuperTab. It doesn't not work properly if you set the same trigger key to complete and snippet. However, it supports nested snippet and longest common string complete. Very promising.

Plugins needs modified:

1. visual_studio.vim
   
   1. needs to update error message format for visual studio 2008 to work (I set it to set errorformat= %#%f(%l) : %#%t%[A-z]%# %m )
   2. needs to change key binding to avoid conflicts with viki.vim ( I changed them from vc to ic)
2. SnipMate.vim
   
   1. needs to update snippets (of course) 

*Update 2010/12/11 for Vim 7.3
*Update 2011/03/10 for delimitMate  
*Update 2011/07/11 for cscope 
*Update 2012/04/24 for neocomplcache 

Add VIM to the right-click menu

The default VIM 7.2 right-click menu will open the new file in the current buffer.
It's quite annoying because I want to open the new file in a new tab most of the time.

To solve the problem, just import the following setting to the windows registery


Windows Registry Editor Version 5.00

[HKEY_CLASSES_ROOT\*\shell\Edit with &Vim\command]
@="\"c:\\Program Files\\Vim\\vim72\\gvim.exe\" -p --remote-tab-silent \"%1\""


SkyMall -- the pleasure of Delta Airline

One of the enjoyful part when I took Delta airline is to browse the skymall shopping magazine.
Theere are always some crazy stuff there.

Like R2D2

And Programmable Gaming Robot

Its pets' solutions

Want to shut your dog up?
Get this

Bark Free Dog Barking Controls

Recent Fun

I recently spent some time playing an old RPG game I got from 2005

Lost Labyrinth!!! 
 
It always gives me a lot of fun to play it.
It is a simple game, but hard enough to be beaten by computers all the time.

Good research demands good data

"Good research demands good data" is what Dr. Su told me when I was a research assistant in Academia Sinica. In the beginning , I thought his word was sarcastic to the computer vision research, since many computer vision papers only work on the data set provided by the authors. Therefore, to be a good research assistant, I tried to make my result work on every video. Then I gave up. I realized that computer vision has its own limitation. Some techniques demand high quality video to make them work.

Recently, on David Lowe's course, he explained how to reduce specular reflection which serious affects the result of stereo matching. He said that there are some papers which propose novel algorithms to detect and reduce the specular reflection effect in images, but the most effective way is to add polarizing filter to your camera. The polarizing filter can reduce specular reflection effect to 0. Instead of producing good vision algorithms, we can put our efforts on obtaining good data. Why not?

Computer Vision: State Of the Art

1. Key point detector
SIFT
ASIFT
SURF

David Lowe reported that SURF is more rebust than SIFT in affine transformation, but SIFT is more robust to 3D rotation.

2. Background subtraction
No state of the art. Though I prefer Mixture of Gaussian personally.

See this
http://www.andrewsenior.com/technical/surveillanceclass/02_MovingObjectDetection_part1.pdf

3. Salient motion detection

see this
http://www.andrewsenior.com/technical/surveillanceclass/03_AdvancedMovingObjectDetection.PDF

4. Stereo

see this
http://vision.middlebury.edu/stereo/eval/

5. Robust estimation

RANSAC -Good if there are many inliers. If not, it needs lost iterations to find a good match
Hough Transform -Use this when RANSAC runs too slow
semi-local constraints -Check the consistency with nearby keypoints

The difference of RANSAC and Hough Transform lies in computation time. Try both to see which one runs faster.

Todo: expand the list, provide all implementations
Reminder: don't spend too much time on paper crawling, do some real stuff

6. Source of training data
ImageNet: A Stanford project to label image by volunteers
http://www.image-net.org/
 Caltech 256
http://www.vision.caltech.edu/Image_Datasets/Caltech256/

Surveillance data: (have ground truth??)
http://pets2006.net/
http://www.elec.qmul.ac.uk/staffinfo/andrea/avss2007_d.html
http://www.nada.kth.se/~hedvig/data.html
http://scienceandresearch.homeoffice.gov.uk/hosdb/cctv-imaging-technology/i-lids/pricing.html

7. Human Attention
A lab of USC doing this. By Prof. Laurent Itti and Prof. Christof Koch
http://ilab.usc.edu/bu/