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Home > Libraries > C > cv.jit > author : Jean-Marc Pelletier

 
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http://www.iamas.ac.jp/~jovan02/cv/download.html

cv.jit is a collection of max/msp/jitter tools for computer vision applications. The goals of this project are to provide externals and abstractions to assist users in tasks such as image segmentation, shape and gesture recognition, motion tracking, etc. as well as to provide educational tools that outline the basics of computer vision techniques.
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cv.jit.perimeter Abstraction Counts the number of edge pixels.

cv.jit.poltocar Abstraction Treats the data in two matrices as polar coordinates and translates to cartesian data.

cv.jit.ravg External Calculates the running average of a matrix over time.

cv.jit.resize External Anti-aliased matrix resize

cv.jit.shapeinfo External This abstraction uses cv.jit.moments to derive more shape descriptors that are easy to understand and useable as is.

cv.jit.shift External Track image regions using MeanShift and CAMShift algorithms.

cv.jit.shift.draw Abstraction Visualization utility for cv.jit.shift.

cv.jit.stddev External Computes the standard deviation of the incoming matrices.

cv.jit.sum External Adds the value of all the cells in each plane and outputs the result in a list. Accepts any data type or planecount.

cv.jit.threshold External Adaptive thresholding.

cv.jit.touches Abstraction Track greyscale/binary image regions.

cv.jit.touches.draw Abstraction Visualize the output of cv.jit.touches.

cv.jit.track External Tracks the position of a number of pixels over time.

cv.jit.track.draw Abstraction Visualize output of cv.jit.track.

cv.jit.trackgroup External This object is used to manage the input and output of cv.jit.track.

cv.jit.trackpoints External This external only accepts the 3-plane float matrices output from cv.jit.track.

cv.jit.undergrad Abstraction Performs simple pattern recognition on incoming lists.

cv.jit.variance External Calculates the variance of the input matrices. The variance is defined as the average of the square of the sample values minus the mean.

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