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Object Detection and Tracking using Computer Vision

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In this livestream, Dr. Matt Rich and Dr. Megan Thompson will show you how to perform one of the more difficult task in computer vision: tracking multiple objects.
Tracking is easy for humans, but difficult for computers. Our brains innately use the current locations and motion of objects to predict their future locations. We recognize that when two people walk past each other, they are different people, and can easily keep them separate. But telling a computer how to do this task is not so simple. In addition to detecting the objects of interest, you need to provide the computer with an estimate of how the objects move and develop an approach to predict their future locations. Your algorithm also needs to be robust to noise and temporarily losing the location of an object.
Matt and Megan will walk through an example from the new Coursera specialization, Computer Vision for Engineering and Science. The code and video used in the example are available to those who sign up for the specialization.
Tracking is easy for humans, but difficult for computers. Our brains innately use the current locations and motion of objects to predict their future locations. We recognize that when two people walk past each other, they are different people, and can easily keep them separate. But telling a computer how to do this task is not so simple. In addition to detecting the objects of interest, you need to provide the computer with an estimate of how the objects move and develop an approach to predict their future locations. Your algorithm also needs to be robust to noise and temporarily losing the location of an object.
Matt and Megan will walk through an example from the new Coursera specialization, Computer Vision for Engineering and Science. The code and video used in the example are available to those who sign up for the specialization.
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