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In this paper, we address the problem of visual tracking in videos without using a pre-learned model of the object. This type of model-free tracking is a hard problem because of limited information about the object, abrupt object motion, and shape deformation. We propose to integrate an object-agnostic prior, called objectness, which is designed to measure the likelihood of a given location to contain...
Starting from an object's location in a video frame, tracking-by-detection methods find the location of that object in a subsequent video frame. The tracker's detection step may produce multiple false positives during short-term occlusions, which can result in loss of track. We propose a tracking-by-detection method that is robust to short-term occlusions and false positives. Here, we extend the Struck...
We propose a method for classifying actions involving people interacting with objects. Our method combines motion and appearance information into a unified framework. Here, we explore the video's sparse component as provided by robust principal-component analysis for the extraction of motion information in the form of trajectories. While we use motion as the main clue for classification, we also incorporate...
Using the critical point theory we are going to prove the existence of one and then of many weak solutions under subtle conditions for impulsive p-Laplacian problem. The novice lies in the fact that we do not restrict ourselves to sublinear impulses. We also prove existence of at least one non-positive and one non-negative solution, when p=2.
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