• Journal of Electrical Engineering and Technology
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• v.11 no.1
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• pp.234-240
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• 2016

We propose a novel framework for markerless camera-based games. By using a visual camera, our method may yield robust human body segmentation with high performance comparable to the segmentation using depth cameras. The edges of human bodies are detected by subtracting gradient backgrounds, and human body regions are segmented by the operations based on mathematical morphology. Collisions between detected regions and virtual objects are determined by finding the colliding time using intra-frame positions of virtual objects. Experimental results show that the proposed method may produce robust segmentation of human bodies, thereby and the collision responses are more accurate than previous methods. Therefore, the proposed framework can be widely used in camera-based games requiring high performance.

• Journal of Electrical Engineering and Technology
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• v.9 no.6
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• pp.2126-2133
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• 2014

We present a scalable object tracking framework, which is capable of removing shadows and tracking the people. The framework consists of background subtraction, fuzzy based shadow removal and boundary tracking algorithm. This work proposes a general-purpose method that combines statistical assumptions with the object-level knowledge of moving objects, apparent objects, and shadows acquired in the processing of the previous frames. Pixels belonging to moving objects and shadows are processed differently in order to supply an object-based selective update. Experimental results demonstrate that the proposed method is able to track the object boundaries under significant shadows with noise and background clutter.

• Journal of Computing Science and Engineering
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• v.7 no.4
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• pp.272-284
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• 2013

In this paper, we propose a new framework for anomaly detection in medical wireless sensor networks, which are used for remote monitoring of patient vital signs. The proposed framework performs sequential data analysis on a mini gateway used as a base station to detect abnormal changes and to cope with unreliable measurements in collected data without prior knowledge of anomalous events or normal data patterns. The proposed approach is based on the Mahalanobis distance for spatial analysis, and a kernel density estimator for the identification of abnormal temporal patterns. Our main objective is to distinguish between faulty measurements and clinical emergencies in order to reduce false alarms triggered by faulty measurements or ill-behaved sensors. Our experimental results on both real and synthetic medical datasets show that the proposed approach can achieve good detection accuracy with a low false alarm rate (less than 5.5%).

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.1
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• pp.19-27
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• 2014

Compressive sensing is an emerging sampling technique which enables sampling a signal at a much lower rate than the Nyquist rate. In this paper, we propose a novel framework based on Kronecker compressive sensing that provides multi-resolution image reconstruction capability. By exploiting the relationship of the sensing matrices between low and high resolution images, the proposed method can reconstruct both high and low resolution images from a single measurement vector. Furthermore, post-processing using BM3D improves its recovery performance. The experimental results showed that the proposed scheme provides significant gains over the conventional framework with respect to the objective and subjective qualities.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.931-939
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• 2003

This paper is aimed at proposing a new framework to predict decision performance, by Investigating decision maker's cognitive resonance. We assume that every decision maker has two kinds of schema­emotional schema and rational schema. Cognitive resonance is believed to have a close relationship with the two schemata and decision performance. In literature on decision performance there is no study' seeking relationship among the two schemata ana cognitive resonance. Therefore, our research purposes are twofold: (1) to provide a theoretical basis for the proposed framework describing the causal relationships among two schemata, cognitive resonance, and decision Performance, and (2) to empirically prove its validity applying to. Internet shopping Situation. Based on the questionnaires from 13S- respondents, we used a second order confirmatory factor analysis (CFA) to extract valid constructs, and structural equation model (SEM) to calculate path coefficients and prove the statistical validity of our proposed research model. Experimental results supported our research model with some further research issues.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.6
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• pp.520-526
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• 2013

This study presents the unit control of a PC (Personal Computer) program using multiple smartphones based on ad hoc communication. A design of the data packet that multiple smartphones send to a computer, and a framework that manages and controls the unit in a computer after analyzing the data packet, are proposed. As a result, multiple users are able to control their own units using their smartphones while seeing the monitor connected to a computer. In other words, multiple users can share the same game in a computer or control their units embedded in a system using their smartphones. An experimental result shows that a racing game in a PC can be realized by the proposed communication interface, where four iPhones are used to control their units in a computer. Thus, the proposed framework can be effectively used for unit control in a PC using multiple smartphones.

• Journal of Communications and Networks
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• v.9 no.1
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• pp.84-92
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• 2007

This paper deals with the creation of multicast trees in a differentiated services (DiffServ) domain. Initially, we model the integration problems of multicast & DiffServ and give a general de-scription of our framework for multicast provisioning in DiffServ domains. Within this framework, we introduce a novel heuristic algorithm which calculates the multicast trees efficiently. The multicast tree's format and the bandwidth constraints per service class are modeled. The heuristic is based on the Dijkstra's shortest path algorithm and aims to produce the cheapest possible trees (Steiner tree problem) that conform to the defined model. The produced trees can be considered as DiffServ-customized Steiner trees. Furthermore, we evaluate the algorithm with theoretical and experimental analysis and finally, we present our conclusions.

• Asia pacific journal of information systems
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• v.21 no.2
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• pp.19-42
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• 2011

This paper proposes a new framework to predict decision performance by investigating the cognitive fit of decision makers. We assume that every decision maker has two kinds of schema: emotional and rational. Cognitive fit is believed to have a close relationship with the two schemata and decision performance. In the literature on decision performance there is few studies investigating the relationship between the two schemata and cognitive fit. Therefore, our research purposes are twofold: (1) to provide a theoretical basis for the proposed framework describing the causal relationships among the two schemata, cognitive fit. and decision performance, and (2) to empirically prove its validity in the application to an Internet shopping environment. Based on the questionnaires from 104 respondents, we used a second order, confirmatory factor analysis (CFA) model to extract valid constructs, and a structural equation model (SEM) to calculate path coefficients and prove the statistical validity of our proposed research model. The experimental results supported our research model.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.433-434
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• 2006

A new disparity estimation method in hierarchical frameworks is proposed. The two main ideas for improving accuracy are to obtain an object boundary map for distinction of homogeneous/object boundary region and to choose adaptive window size/shapes. Moreover, for the reduction of computational complexity, we change reference regions in hierarchical framework. The experimental results show that the proposed method can acquire good results which are robust to homogeneous and object boundary regions.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2015.11a
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• pp.180-181
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• 2015

In this paper, we present a consistent and efficient edit propagation method that is applied for light field data. Unlike conventional sparse edit propagation, the coherency between light field sub-aperture images is fully considered by utilizing light field consistency in the optimization framework. Instead of directly solving the optimization function on all light field sub-aperture images, the proposed optimization framework performs sparse edit propagation in the extended focus image domain. The extended focus image is the representative image that contains implicit depth information and the well-focused region of all sub-aperture images. The edit results in the extended focus image are then propagated back to each light field sub-aperture image. Experimental results on test images captured by a Lytro off-the-shelf light field camera confirm that the proposed method provides robust and consistent results of edited light field sub-aperture images.