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Object tracking in videos is one of the most challenging tasks in machine learning. It's due to appearance changes caused by variable illumination, occlusion and variation shifts. The conventional algorithms developed by researchers are able to tackle only some of the issues in object tracking; however, they still do not provide a foolproof solution.
This Whitepaper examines various video tracking approaches including Deep Learning for multiple object tracking, Convolutional Neural Network based online and offline training trackers and CNN + LSTM based detection video object trackers.