pattern-recognition

I am attempting to create a program that can find human figures in video of game play of call of duty. I have compiled a list of ~2200 separate images from this video that either contain a human figure or do not. I have then attempted to train a neural network to tell the difference between the two sets of images. Then, I divide each video frame up into a couple hundred gridded rectangles and I check each with my ANN. The rectangles are overlapping to attempt to capture figures that are between grid rects, but this doesn't seem to work well. So I have a few questions: Are neural networks the

I have nothing useful to do and was playing with jigsaw puzzle like this: alt text http://manual.gimp.org/nl/images/filters/examples/render-taj-jigsaw.jpg and I was wondering if it'd be possible to make a program that assists me in putting it together. Imagine that I have a small puzzle, like 4x3 pieces, but the little tabs and blanks are non-uniform - different pieces have these tabs in different height, of different shape, of different size. What I'd do is to take pictures of all of these pieces, let a program analyze them and store their attributes somewhere. Then, when I pick up a piece, I

What would you recommend for recognizing all characters from a screenshot? The screenshot is perfectly clear (only black text on a white background), also I can choose any standard font for the text (installed on Windows). I have tried some OCR ways (Tesseract and such), but it made mistakes in recognizing some characters (that baffled me, as the text is without slightest noise, and the fonts were some most common ones - Courier New, Fixedsys etc.), and I need it to be 100% accurate. Is there some library available for this specific purpose, some pattern recognition or something? or should I

I've been looking around for some papers (or info) on this topic. To avoid a misunderstanding: I'm not talking about finding a supplied pattern in multiple locations. Repeating patterns can also be understood to mean repeating images. The definition of pattern here isn't abstract. Imagine, for instance, a brick wall. The wall is composed of individual bricks. A picture of the wall is composed of the repeating image of a brick. The solution must preferably find the largest repeating pattern. Large in this context can be defined two ways: pixel area or number of repetitions. In the above example

So you have an array 1 2 3 60 70 80 100 220 230 250 For a better understanding: How would you group/cluster the three areas in arrays in python(v2.6), so you get three arrays in this case containing [1 2 3] [60 70 80 100] [220 230 250] Background: y-axis is frequency, x-axis is number. These numbers are the ten highest amplitudes being represented by their frequencies. I want to create three discrete numbers from them for pattern recognition. There could be many more points but all of them are grouped by a relatively big frequency difference as you can see in this example between about 50 and

I would like to synchronize a spoken recording against a known text. Is there a speech-to-text / natural language processing library that would facilitate this? I imagine I'd want to detect word boundaries and compute candidate matches from a dictionary. Most of the questions I've found on SO concern written language. Desired, but not required: Open Source Compatible with American English out-of-the-box Cross-platform Thoroughly documented Edit: I realize this is a very broad, even naive, question, so thanks in advance for your guidance. What I've found so far: OpenEars (iOS Sphinx/Flite

Update this question was previously titled as " Give me the name of a simple algorithm for signal(sound) pattern detection " My objective is to detect the presence of a given pattern in a noisy signal. I want to detect the presence of a species of insect recording the sounds with a microphone. I have previously recorded the sound of the insect in a digital format. I am not trying to do voice recognition. I am already using convolution between the input signal and the pattern to determine their similarity level. But I think that this technique is more suited to discrete time (i.e. digital

I have a basic understanding in image processing and now studying in-depth the "Digital Image Processing" book by Gonzales. When image given and object of interest approximated form is known (e.g. circle, triangle), what is the best algorithm / method to find this object on image? The object can be slightly deformed, so brute force approach will not help. You may try using Histograms of Oriented Gradients (also called Edge Orientation Histograms). We have used them for detecting road signs. http://en.wikipedia.org/wiki/Histogram_of_oriented_gradients and the papers by Bill Triggs should get

I'm interested in learning more about pattern recognition. I know that's somewhat of a broad field, so I'll list some specific types of problems I would like to learn to deal with: Finding patterns in a seemingly random set of bytes. Recognizing known shapes (such as circles and squares) in images. Noticing movement patterns given a stream of positions (Vector3) This is a new area of experimentation for me personally, and to be honest, I simply don't know where to start :-) I'm obviously not looking for the answers to be provided to me on a silver platter, but some search terms and/or online