![]() ![]() ![]() The way I solved the problem of aggregating contours with a high degree of affinity (e.g., multiple contours that describe a single object) was to implement a partitioned, non-hierarchical agglomerative clustering approach, thanks to the thoughtful suggestion by Ĭalculate a closeness factor for all contour pairs (distance between centers of contours minus the radii of both contours) Question: Is there a method by which the nearness of contours can be evaluated, so as to group them into a larger contour/object?Īre there approaches to solving this problem? Below are images that illustrate the issue under consideration My approach is leaning towards grouping contours that have some measure of nearness, though for people, the vertical elongation can be a complication for nearness calculations. (I am addressing the shadow issue in a different thread) I am not able to reliable draw a rect around the full object in order to use that smaller window in which to detect features (or classifier, HOG, etc). On top of that, there are sometime multiple objects (eg., person with dog) moving through the video stream. The contours rarely completely enclose the subject, consisting instead of a number of contours that usually partially map to the subject. I've tried BackgroundSubtractorMOG and MOG2 with varying parameters (may not have tried the right combinations) along with erode/dilate and findContours(). Problem: Too many fragmented contours for each object almost all the time. value - Color of border if border type is cv.Overall Objective: Create Regions of Interest (ROIs) in order to then examine them for objects such as person, dog, vehicle utilizing the Java bindingsĪpproach: BackgroundSubtraction -> FindContours -> downselect to Region of Interest (smallest encompassing rectangle around contours of an object) that is then sent to be classified and/or recognized.cv.BORDER_WRAP - Can't explain, it will look like this : cdefgh|abcdefgh|abcdefg.cv.BORDER_REPLICATE - Last element is replicated throughout, like this: aaaaaa|abcdefgh|hhhhhhh.cv.BORDER_REFLECT_101 or cv.BORDER_DEFAULT - Same as above, but with a slight change, like this : gfedcb|abcdefgh|gfedcba. ![]() cv.BORDER_REFLECT - Border will be mirror reflection of the border elements, like this : fedcba|abcdefgh|hgfedcb.The value should be given as next argument. cv.BORDER_CONSTANT - Adds a constant colored border.borderType - Flag defining what kind of border to be added.top, bottom, left, right - border width in number of pixels in corresponding directions.But it has more applications for convolution operation, zero padding etc. If you want to create a border around an image, something like a photo frame, you can use cv.copyMakeBorder(). Cv.split() is a costly operation (in terms of time). ![]()
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