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Logistic Classifier The logistic classifier is similar to equation of the plane. W is weight vector, X is input vector and y is output... -
As you can see in the following video, I created a class that stitching n cameras in real time. https://www.youtube.com/user/feelmare/sear...
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* Introduction - The solution shows panorama image from multi images. The panorama images is processing by real-time stitching algorithm... -
Image size of origin is 320*240. Processing time is 30.96 second took. The result of stitching The resul... -
fig 1. Left: set 4 points (Left Top, Right Top, Right Bottom, Left Bottom), right:warped image to (0,0) (300,0), (300,300), (0,300) Fi... -
Created Date : 2011.10 Language : C/C++ Tool : Microsoft Visual C++ 2008 Library & Utilized : OpenCV 2.3 Reference : SIFT referenc... -
OpenCV has AdaBoost algorithm function. And gpu version also is provided. For using detection, we prepare the trained xml file. Although... -
I once wrote the following article. http://study.marearts.com/2014/04/opencv-study-mat-point-access-method.html This article is a sample c... -
Created Date : 2011.8 Language : Matlab Tool : Matlab 2010 Library & Utilized : - Reference : Multiple View Geometry (Hartly and Z... -
Proceed with the project to update the 2012 version, or that you must reinstall Visual Studio 2010. If you are using Visual Studio 2...
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ReplyDeleteThis one is better than "More stringent pedestrian detection by Deep learning verification" and "More stringent pedestrian detection by HOG verification". Do you use OpenCV to achieve such result?
ReplyDeleteDetecting pedestrian using Deep learning is recorded high rate false positive, but not sensitive variable pedestrian pose. and processing speed is not good.
DeleteHog is fast, but to detect typical appearance when training data pose.
So, I can not say yet, which way is better..
Thank you.
can you share this source code! Thank you
ReplyDelete