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Google Coral USB Edge TPU Implementation Guide 1. Installation and Troubleshooting 1.1 Hardware Requirements Google Coral USB Accelerator ...
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Image size of origin is 320*240. Processing time is 30.96 second took. The result of stitching The resul... -
This is data acquisition source code of LMS511(SICK co.) Source code is made by MFC(vs 2008). The sensor is communicated by TCP/IP. ... -
I use MOG2 algorithm to background subtraction. The process is resize to small for more fast processing to blur for avoid noise affectio...
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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... -
* Introduction - The solution shows panorama image from multi images. The panorama images is processing by real-time stitching algorithm... -
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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In past, I wrote an articel about YUV 444, 422, 411 introduction and yuv rgb converting example code. refer to this page -> http://feel...
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This example source code is to extract HOG feature from images. And save descriptors to XML file. The source code explain how to use HOGD...
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Created Date : 2011.2 Language : C/C++ Tool : Microsoft Visual C++ 2010 Library & Utilized : OpenCV 2.2 Reference : Interent Refer...
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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