A new version of OpenCV has been released so… Time to update! (This is an updated version of the article I wrote months ago: Installing and using OpenCV 3.2 with Eclipse and MinGW on Windows 10.
And the second conclusion. The bottleneck of the current Python code is the video frame capture speed. Fortunately for us, the frame capture efficiency is roughly equal to the depth map calculation efficiency (about 20 frames per second in both cases). But we left a few loopholes for those who need more speed when capturing frames.
Dec 19, 2013 · The idea is to keep track of an object from on several consecutive frames, this may become difficult if the object is moving fast in relation to the frame rate of the camera. The initial purpose of the project was to measure the customers interests towards an advertising by using the OpenCV library.
Emergence of new consumer-level cameras capable of capturing video in 60 fps challenges this tradeoff even further. Unfortunately, state-of-the-art tracking techniques struggle to meet frame rates over 30 VGA-resolution fps with standard desktop power, let alone on typically-weaker mobile devices.
For the same VGG-16 model, Faster R-CNN has a frame rate of 5 fps on a GPU while achieving state-of-the-art object detection accuracy. The RPN is a kind of a fully convolutional network and can be trained end-to-end specifically for the task of generating detection proposals and is designed to efficiently predict region proposals with a wide ...
Dec 18, 2017 · DFK AFU420-L62 Specification GENERAL BEHAVIOR Dynamic range 8/12 bit Video formats @ frame rate (maximum) 7,728×5,368 (41.5 MP) RGB32 @ 7 fps 5,424×5,360 (29.1 MP) RGB32 @ 10 fps
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