Hello out there, I have been working on a project to design a new computer vision system and I have succeeded, the only stage remaining is the homography estimation stage.But to estimate the homography matrix the algorithm has to compute the singular value decomposition or svd of the measurement matrix. I can easily use openCV or LAPACK for that but I want to implement my own Jacobi SVD method and the openCV and Lapack are too big, I don't want my computer vision system library to be dependent on them. Does anyone have a copyright free example code of a fast jacobi svd implementation that I can modify without using the big free libraries? I want a simplified implementation, even pseudocode would suffice.
I will create a tech demo video for this computer vision system. It out performs state of the art systems in object detection/recognition. I'am surely going to acknowledge any help I can get.
Thanks in advance.
“Everything is simple when you take your time to analyze it.”
i am doing a language translation app to convert trini vernacular in to standard english.. i have just started.. i am considering to use the boyer more algorithm to do the matching.. is this a good idea? and what else can any one suggest?
Boyer Moore string searching is efficient for searching large volumes of text, but translation usually involves more than just mechanically replacing one set of strings with another. You might want to look at Lex and Yacc, e.g. http://dinosaur.compilertools.net/[^]
hey thank you soo much... this really gives me a good head start.. ... i dont have any IT experience in working , but to tell the truth i love it.. it intrigues me alot.. hence the reason why i am doing my degree in computing and information systems...... the links u sent me is awe some.. i will keep asking questions... please dont laugh if i ask questions that you may think is foolish lol.. because like i said im really new.. my project is dues in may and i have alot of work to put out u knw...
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