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Video surveillance over a long span of time is no longer a luxury in this day and age. The abundance of video data captured over time presents a slew of new problems in computer vision. One potential challenge involves the task of finding anomalous tracks over a long period of time. In this work, we propose a new time-scale framework for mining anomalous(More)
What good are surveillance videos without knowing what objects are there? Object classification has been actively researched for images and more recently, for videos, but not in the long-term sense. Videos that span a long period of time has its arduous challenges in such a task. This paper intends to bridge that gap by exploring object classification in(More)
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