" (Project ID: 1251-745-57892). The authors would also like to thank the NVIDIA Corporation for the donation of a TITAN XP GPU used in these experiments. We would also like to acknowledge the grant provided by Comision Fulbright Colombia to fund the Visiting Scholar Scholarship granted to H.D.B.-R.

No abstract

The existing body of work on video object tracking (VOT) algorithms has studied various image conditions such as occlusion, clutter, and object shape, which influence video quality and affect tracking performance. Nonetheless, there is no clear distinction between the performance reduction caused by scene-dependent challenges such as occlusion and clutter, and the effect of authentic in-capture and postcapture distortions. Despite the plethora of VOT methods in the literature, there is a lack of detailed studies analyzing the performance of videos with authentic in-capture and post-capture distortions. We introduced a new dataset of authentically distorted videos (AD-SVD) to address this issue. This dataset contains 4476 videos with different authentic distortions and surveillance activities. Furthermore, it provides benchmarking results for evaluating ten state-of-the-art visual object trackers (from VOT 2017-2018 challenges) based on the proposed dataset. In addition, this study develops an approach for performance prediction and qualityaware feature selection for single-object tracking in authentically distorted surveillance videos. The method predicts the performance of a VOT algorithm with high accuracy. Then, the probability of obtaining the reference output is maximized without executing the tracking algorithms. We also propose a framework to reduce video tracker computation resources (time and video storage space). We achieve this by balancing processing time and tracking accuracy by predicting the performance in a range of spatial resolutions. This approach can reduce the execution time by up to 34% with a slight decrease in performance of 3%.INDEX TERMS Video Object Tracking, in-capture and post-capture distortions, video quality assessment, video tracking prediction.

We provide sufficient conditions for the existence of periodic solutions for an idealized electrostatic actuator modeled by the Liénard-type equation x ¨ + F D x , x ̇ + x = β V 2 t / 1 − x 2 , x ∈ − ∞ , 1 with β ∈ ℝ + , V ∈ C ℝ / T ℤ , and F D x , x ̇ = κ x ̇ / 1 − x 3 , κ ∈ ℝ + (called squeeze film damping force), or F D x , x ̇ = c x ̇ , c ∈ ℝ + (called linear damping force). If F D is of squeeze film type, we have proven that there exists at least two positive periodic solutions, one of them locally asymptotically stable. Meanwhile, if F D is a linear damping force, we have proven that there are only two positive periodic solutions. One is unstable, and the other is locally exponentially asymptotically stable with rate of decay of c / 2 . Our technique can be applied to a class of Liénard equations that model several microelectromechanical system devices, including the comb-drive finger model and torsional actuators.