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Closed 11 years ago.
I am looking at The Special Effects In Picasa article.
Where can I find the following:
C/C++ or Java open source library to do it
Good books and/or articles to learn the algorithms how to do it myself
Thanks in advance for your help.
You can achieve most of the effects on that page by color manipulation (white balance) and spatial filtering.
Before you go down the path of using libraries to achieve this, I recommend playing around with image manipulation software like GIMP and trying to replicate the effects. After you're sure you know what you're doing, go ahead and try and code it up.
For libraries, have a look at opencv. There are also Java wrappers for that library if that is your language of choice (Java has its own imaging libraries as well, but I haven't used them). For books, my personal favorite is Gonzalez & Woods -- the first few chapters will get you started. For articles, Google is your friend.
Related
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Closed 10 years ago.
I know that AI is vast field and there are many algorithms which exist there.
I have tried learning from wikipedia but thats too much math stuff which i didn't understand.
Is there any place from where i can find the 7-8 lines of brief introduction on each algorithm and which can tell me that for which type of problems we can use which algorithm.
E,g something like IF we need to find some shortest route t0o some destination then we can use shortest path algorithm. Currently there are so much variery of fields like Bayesian methods , meakov chain models , optimization algorithms which i am not able to get what type of proeblems can be solved by them.
I jsut want to know what athey are capable of doi ng rather than hard core math stuff which always goes on the top of my head
aaai.org has some good introductory articles.
http://aitopics.net/AIOverview
machine learning 101: https://stackoverflow.com/questions/598726/overwhelmed-by-machine-learning-is-there-an-ml101-book/598772#598772
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Closed 10 years ago.
My C and Objective-C skills are ok but i really could do with a better grasp on building binary's and libraries using configure and make files. Is there a book or consolidated reference I should be aiming to look at. Ive googled but given the generic nature of the search terms and plethora of related information i would be grateful if someone could point me at a recommended source
The autoconf manual is the authoritative source of information on writing configure scripts, and includes sections on portable 'make' and shell programming. As well as being a reference, it also contains a reasonable tutorial.
If you want to build libraries as well, then you want to look at libtool, but unfortunately libtool can be a bit of a beast to work with unless you're also using automake, so this is turning into a rather long reading list.
O'Reilly have a book called 'Autotools'. I don't know it, but given my experience with other O'Reilly books, that's the first I'd take off the shelf and browse through.
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Closed 10 years ago.
I am looking for a book where some monocular/visual SLAM is described and implemented.
Can you list and recommend some?
I'd like to use OpenCV but that is not a requirement.
I don't know of a book with a description of such an algorithm, but there's a complete open source implementation (in C++) of a vslam system available as part of the Robot Operating System. It uses SURF descriptors and vocabulary trees for place recognition, and bundle adjustment for SLAM. It does use OpenCV heavily as it's made by the same people. See the website here. I can't say for sure as they don't mention and I haven't looked in great detail, but their implementation seems to be based on, or at least is similar to, this paper.
Edit: The paper linked above was actually written by the people who implemented the vslam system given above, it appears. So it is definitely a good resource for understanding it.
I don't know about a book, but maybe PTAM can be useful. The ISMAR 2007 paper by Klein has a description about the system and the source code is available so you can check the details.
Of course, PTAM is just a (good) method in the SLAM field.
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Closed 10 years ago.
Can someone recommend me some good bibliographic material regarding template matching algorithms and techniques? (book, articles, matlab functions)
http://www.hoepli.it/libro/fundamentals-of-digital-image-processing/9780470844731.asp
http://oreilly.com/catalog/9780596516130
i've bought these 2 books for my thesis, template matching is well explained (especially in the first one).
i also suggest http://www.araa.asn.au/acra/acra2004/papers/cole.pdf which is a well written article (from wikipedia) and maybe check out the OpenSURF (c++ library for features extraction) paper http://www.chrisevansdev.com/computer-vision-opensurf.html
Functions for template matching in software systems:
Matlab offers normxcorr2 to perform normalized cross correlation.
Mathematica offers the function ImageCorrelate. Its third argument covers all the classical distance functions used in template matching:
http://reference.wolfram.com/mathematica/ref/ImageCorrelate.html
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Closed 11 years ago.
I need a good stemming algorithm for a project I'm working on. It was suggested that I look at the Porter Stemmer. When I checked out the page on the Porter stemmer I found that it is deprecated now in favor of the "Snowball" stemmer.
I need a good stemmer, but I can't really spend significant time implementing (or optimizing) my own. What is the best "off the shelf", freely available stemmer? Are there any non-free stemmers available for a reasonable price? Or, is the Snowball stemmer my best bet?
The Porter2 stemmer is the one I've decided to go with. It seemed the porter stemmer was the standard, but when I found the page by the author he recommended the "Snowball (Porter2)" stemmer. There is a C port link on this page.
It really depends on how you're planning to apply it. The Natural Language Toolkit (http://nltk.sourceforge.net) has a number of stemmers implemented in it that should be able to handle most applications. I prefer the Morphy stemmer.
Of course, it's available in Python, so if you're working with another language, you can always look through the code to glean the algorithm and transfer it to your language of choice. Python is highly readable.