Measurement Biases in Pseudo Steady-State Processes Sriram Devanathan, Stephen B. Vardeman and Derrick K. Rollins, Sr. Department of Chemical Engineering, Iowa State University, Ames, Iowa 50011 Departments of Statistics, Ames, Iowa 50011 Department of Industrial and Manufacturing Systems and Engineering, Ames, Iowa 50011 *Author to whom correspondence should be sent Abstract Two new approaches...

Tracking multiple objects in surveillance scenarios involves considerable difficulty because of occlusions. We report a composite tracker based on feature tracking and colour based tracking that demonstrates superior performance under high degrees of occlusion. Disjoint foreground blobs are extracted by using change masks obtained by combining an online-updated background model and flow informa...

Traditional mean shift method has the limitation that could not effectively adjust kernel bandwidth to represent object accurately. To address this problem, in this paper, we propose a novel contour tracking algorithm using a determined binary level set model (DBLSM) based on mean shift procedure. In contrast with other previous work, the computational efficiency is greatly improved due to the ...

In this paper, we compare and evaluate five contemporary, data-driven real-time 2D object tracking methods: the region tracker by Hager et al., the Hyperplane tracker, the CONDENSATION tracker, and the Mean Shift and Trust Region trackers. The first two are classical template based methods, while the latter three are from the more recently proposed class of histogram based trackers. All tracker...

We evaluated the effects of faking on mean scores and correlations with self-reported counterproductive behavior of integrity-related personality items administered in single-stimulus and forced-choice formats. In laboratory studies, we found that respondents instructed to respond as if applying for a job scored higher than when given standard or “straight-take” instructions. The size of the me...

In this paper, we present case deletion and mean shift outlier models for linear mixed measurement error models using the corrected likelihood of Nakamura (1990). We derive the corrected score test statistic for outliers detection based on mean shift outlier models. Furthermore, several case deletion diagnostics are constructed as a tool for influence diagnostics. It is found that they can be w...

In background subtraction, the maintenance of significant backgrounds is very critical under various scene changes. In this paper, we propose a background maintenance method for dynamic scenes including global intensity level changes caused by the changes of illumination conditions and camera settings. If global intensity level changes abruptly, the conventional background model cannot discrimi...

Object tracking in real time videos is a critical task .So far many algorithms have been proposed to overcome the difficulties which arises from noise, occlusions and changes in the foreground object. But still there is a need for an efficient algorithm that can effectively track the object due to its varying position under various ambient conditions. Among various tracking methods, the mean sh...

This paper proposes a novel framework for robust click-point linking: efficient localized registration that allows users to interactively prescribe where the accuracy has to be high. Given a user-specified point in one domain, it estimates a single point-wise correspondence between a data domain pair. In order to link visually dissimilar local regions, we propose a new strategy that robustly es...

A framework for real-time tracking of complex non-rigid objects is presented. The object shape is approximated by an ellipse and its appearance by histogram based features derived from local image properties. An efficient search procedure is used to find the image region with a histogram most similar to the histogram of the tracked object. The procedure is a natural extension of the mean-shift ...