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Real-Time Moving Object Detection and Tracking Using SURF
Real-Time Moving Object Detection and Tracking Using Speed Up Robust Features (SURF)
Angielski
78 b
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Object detection and tracking is one of the most researched areas in computer vision and is receiving a growing attention because of its wide areas of applications which include surveillance, industrial inspection, robotics, mobiles, and 3D gaming among others. Object detection and tracking can be done using variety of tools available such OpenCV developed by Intel, officially launched in the year 1999, Emgu CV, Matlab, etc. The OpenCV library contains over 500 functions that cover many areas in vision, product inspection, medical imaging, security, user interface, camera calibration, stereo vision and robotics. The Real- Time Moving Object Detection and Tracking System algorithm is developed in Microsoft Visual Basic 2010 express edition using Speed Up Robust Features available in OpenCV and EmguCV libraries which are used for the image processing and computer vision tasks. A Logitech C310 High Definition (HD) webcam with 5 Mega Pixel (MP) is used for the purpose of real-time detection and tracking. The system can detect an object from a still image containing many other objects as well as detect and track objects using WebCam.
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