• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.4C
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• pp.277-282
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• 2012

In this paper, we present a real-time eye contact system for realistic telepresence using a Kinect depth camera. In order to generate the eye contact image, we capture a pair of color and depth video. Then, the foreground single user is separated from the background. Since the raw depth data includes several types of noises, we perform a joint bilateral filtering method. We apply the discontinuity-adaptive depth filter to the filtered depth map to reduce the disocclusion area. From the color image and the preprocessed depth map, we construct a user mesh model at the virtual viewpoint. The entire system is implemented through GPU-based parallel programming for real-time processing. Experimental results have shown that the proposed eye contact system is efficient in realizing eye contact, providing the realistic telepresence.

• Journal of Construction Engineering and Project Management
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• v.5 no.2
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• pp.11-15
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• 2015

The Last PlannerSystem (LPS) has been implemented on construction projects to increase work flow reliability, a precondition for project performance againstproductivity and progress targets. The LPS encompasses four tiers of planning processes:master scheduling, phase scheduling, lookahead planning, and commitment / weeklywork planning. This research highlights deficiencies in the current implementation of LPS including poor lookahead planning which results in poor linkage between weeklywork plans and the master schedule. This poor linkage undetermines the ability of theweekly work planning process to select for execution tasks that are critical to projectsuccess. As a result, percent plan complete (PPC) becomes a weak indicator of project progress. The purpose of this research is to improve lookahead planning (the bridgebetween weekly work planning and master scheduling), improve PPC, and improve theselection of tasks that are critical to project success by increasing the link betweenShould, Can, Will, and Did (components of the LPS), thereby rendering PPC a betterindicator of project progress. The research employs the case study research method to describe deficiencies inthe current implementation of the LPS and suggest guidelines for a better application ofLPS in general and lookahead planning in particular. It then introduces an analyticalsimulation model to analyze the lookahead planning process. This is done by examining the impact on PPC of increasing two lookahead planning performance metrics: tasksanticipated (TA) and tasks made ready (TMR). Finally, the research investigates theimportance of the lookahead planning functions: identification and removal ofconstraints, task breakdown, and operations design.The research findings confirm the positive impact of improving lookaheadplanning (i.e., TA and TMR) on PPC. It also recognizes the need to perform lookaheadplanning differently for three types of work involving different levels of uncertainty:stable work, medium uncertainty work, and highly emergent work.The research confirms the LPS rules for practice and specifically the need to planin greater detail as time gets closer to performing the work. It highlights the role of LPSas a production system that incorporates deliberate planning (predetermined andoptimized) and situated planning (flexible and adaptive). Finally, the research presents recommendations for production planningimprovements in three areas: process related, (suggesting guidelines for practice),technical, (highlighting issues with current software programs and advocating theinclusion of collaborative planning capability), and organizational improvements(suggesting transitional steps when applying the LPS).

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.71-79
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• 2011

The objective of the imaging pipeline is to transform the original scene into a display image that appear similar, Generally, gamma adjustment or histogram-based method is modified to improve the contrast and detail. However, this is insufficient as the intensity and the chromaticity of illumination vary with geometric position. Thus, MSR (Multi-Scale Retinex) has been proposed. the MSR is based on a channel-independent logarithm, and it is dependent on the scale of the Gaussian filter, which varies according to input image. Therefore, after correcting the color, image quality degradations, such as halo, graying-out, and dominated color, may occur. Accordingly, this paper presents a novel color correction method using a modified image formation model in which the image is divided into three components such as global illumination, local illumination, and reflectance. The global illumination is obtained through Gaussian filtering of the original image, and the local illumination is estimated by using JND-based adaptive filter. Thereafter, the reflectance is estimated by dividing the original image by the estimated global and the local illumination to remove the influence of the illumination effects. The output image is obtained based on sRGB color representation. The experiment results show that the proposed method yields better performance of color correction over the conventional methods.