University of Central Florida

About: University of Central Florida is a education organization based out in Orlando, Florida, United States. It is known for research contribution in the topics: Laser & Population. The organization has 18822 authors who have published 48679 publications receiving 1234422 citations. The organization is also known as: UCF.

Consistent labeling of tracked objects in multiple cameras with overlapping fields of view

Abstract: We address the issue of tracking moving objects in an environment covered by multiple uncalibrated cameras with overlapping fields of view, typical of most surveillance setups. In such a scenario, it is essential to establish correspondence between tracks of the same object, seen in different cameras, to recover complete information about the object. We call this the problem of consistent labeling of objects when seen in multiple cameras. We employ a novel approach of finding the limits of field of view (FOV) of each camera as visible in the other cameras. We show that, if the FOV lines are known, it is possible to disambiguate between multiple possibilities for correspondence. We present a method to automatically recover these lines by observing motion in the environment, Furthermore, once these lines are initialized, the homography between the views can also be recovered. We present results on indoor and outdoor sequences containing persons and vehicles.

A Meta-Analysis of Factors Influencing the Development of Trust in Automation: Implications for Understanding Autonomy in Future Systems

Abstract: Objective:We used meta-analysis to assess research concerning human trust in automation to understand the foundation upon which future autonomous systems can be built.Background:Trust is increasingly important in the growing need for synergistic human–machine teaming. Thus, we expand on our previous meta-analytic foundation in the field of human–robot interaction to include all of automation interaction.Method:We used meta-analysis to assess trust in automation. Thirty studies provided 164 pairwise effect sizes, and 16 studies provided 63 correlational effect sizes.Results:The overall effect size of all factors on trust development was ḡ = +0.48, and the correlational effect was r¯ = +0.34, each of which represented medium effects. Moderator effects were observed for the human-related (ḡ = +0.49; r¯ = +0.16) and automation-related (ḡ = +0.53; r¯ = +0.41) factors. Moderator effects specific to environmental factors proved insufficient in number to calculate at this time.Conclusion:Findings provide a quan...

Panel LM Unit-root Tests with Level Shifts*

Abstract: This paper proposes a new panel unit‐root test based on the Lagrangian multiplier (LM) principle. We show that the asymptotic distribution of the new panel LM test is not affected by the presence of structural shifts. This result holds under a mild condition that N/T→k, where k is any finite constant. Our simulation study shows that the panel LM unit‐root test is not only robust to the presence of structural shifts, but is more powerful than the popular Im, Pesaran and Shin (IPS) test. We apply our new test to the purchasing power parity (PPP) hypothesis and find strong evidence for PPP.

Power System Dynamic State Estimation: Motivations, Definitions, Methodologies, and Future Work

Abstract: This paper summarizes the technical activities of the Task Force on Power System Dynamic State and Parameter Estimation. This Task Force was established by the IEEE Working Group on State Estimation Algorithms to investigate the added benefits of dynamic state and parameter estimation for the enhancement of the reliability, security, and resilience of electric power systems. The motivations and engineering values of dynamic state estimation (DSE) are discussed in detail. Then, a set of potential applications that will rely on DSE is presented and discussed. Furthermore, a unified framework is proposed to clarify the important concepts related to DSE, forecasting-aided state estimation, tracking state estimation, and static state estimation. An overview of the current progress in DSE and dynamic parameter estimation is provided. The paper also provides future research needs and directions for the power engineering community.