Abstract
The emerging technology revolution empowered by artificial intelligence related research has brought us closer to the implementation of systems only seen in science-faction movies before. Artificial vision systems built in complex modern artefacts are very important for supporting their execution and perception based on camera captured raw pixels is one of the keys to open the machine intelligence. Deep learning and visual object tracking are both hot topics for computer vision research in recent years. Many visual object tracking algorithms based on deep learning technique appeared. The effectiveness of deep features for visual tracking has been shown on benchmarks, these big guys showed more intelligent behaviour capturing target object in bounding box but the high computational cost and deep hungry for data contradicts our initial requirements for practical tracking algorithm. In this paper, we investigated several deep trackers to help discovering current trends in this research area and hope it could help researchers and practitioners to better understand and further enhance existing methods.
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