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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... -
RTSP(Real Time Streaming Protocol) is video streaming, it usually sent from network camera. VideoCapture function in opencv also can get r...
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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... -
This article explain how to access the thread index when you make block and thread with two dimensions. please refer to this page about me... -
In the YUV color format, Y is bright information, U is blue color area, V is red color area. Show the below picture. The picture is u-v col... -
* 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... -
This is example of SVM learning method. This example is I already have explained in past time. See the this page - > http://feelmare.bl...
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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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This source code based on -> http://feelmare.blogspot.kr/2011/08/two-image-mosaic-paranoma-based-on-sift.html This link page introduces...
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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