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Automatic refinement strategies for manual initialization of object trackers

Zhu, Hao; Porikli, Fatih


Tracking objects across multiple frames is a well-investigated problem in computer vision. The majority of the existing algorithms that assume an accurate initialization is readily available. However, in many real-life settings, in particular for applications where the video is streaming in real time, the initialization has to be provided by a human operator. This limitation raises an inevitable uncertainty issue. Here, we first collect a large and new data set of inputs that consists of...[Show more]

CollectionsANU Research Publications
Date published: 2017
Type: Journal article
Source: IEEE Transactions on Image Processing
DOI: 10.1109/TIP.2016.2633874


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