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The MNIST dataset is a dataset of handwritten digits, comprising 60 000 training examples and 10 000 test examples. The dataset can be downl... -
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... -
make well divided linear coordinate And make pair coordinate Please see code for detail explanation. import numpy as np import cv2 ... -
setTo masking example gist start gist end CopyTo masking example gist start gist end -
Logistic Classifier The logistic classifier is similar to equation of the plane. W is weight vector, X is input vector and y is output... -
//Singular value decomposition : Mat w, u, v; SVDecomp(data, w, u, v); // A = U W V^T //The flags cause U and V to be returned transpose...
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'meanshift' is clustering algorithm. It can be used color segmentation, color tracking.. This article is about color segmentation ... -
Image size of origin is 320*240. Processing time is 30.96 second took. The result of stitching The resul... -
Video stabilization example source code. The principle is like that... Firstly, to obtain 2 adjacent images extract good feature to t...
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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