• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.69-72
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• 2001

This paper proposes a positional estimation method for extracted line features by stereo vision. Based on given reference plane, planar surfaces corresponding the given plane are first extracted. Then, features in the planar surfaces are selected. Using the Extended Kalman Filter the feature positions are estimated by combining area- and feature-based stereo matching results. Experimental results show the proposed method is feasible.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.10
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• pp.502-510
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• 2007

Private Matching is a problem of computing the intersection of private datasets of two parties. One could envision the usage of private matching for Insurance fraud detection system, Do-not-fly list, medical databases, and many other applications. In 2004, Freedman et at. [1] introduced a probabilistic solution for this problem, and they extended it to malicious adversary model and multi-party computation. In this paper, we propose a new deterministic protocol for private matching with perfect correctness. We apply this technique to adversary models, achieving more reliable and higher speed computation.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.9
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• pp.916-921
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• 2011

Mobile robot localization is the task of estimating the robot pose in a given environment. This research deals with outdoor localization based on an elevation map. Since outdoor environments are large and contain many complex objects, it is difficult to robustly estimate the robot pose. This paper proposes a Hausdorff distance-based map matching method. The Hausdorff distance is exploited to measure the similarity between extracted features obtained from the robot and elevation map. The experiments and simulations show that the proposed Hausdorff distance-based map matching is useful for robust outdoor localization using an elevation map. Also, it can be easily applied to other probabilistic approaches such as a Markov localization method.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10a
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• pp.484-489
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• 2006

Private Matching은 각기 다른 두 참여자 (two-party)가 가진 데이터의 교집합 (intersection)을 구하는 문제이다. Private matching은 보험사기 방지시스템 (insurance fraud detection system), 의료정보 검색, 항공기 탐승 금지자 목록 (Do-not-fly list) 검색 등에 이용될 수 있으며 다자간의 계산 (multiparty computation)으로 확장하면 전자투표, 온라인 게임 등에도 이용될 수 있다. 2004년 Freedman 등은 이 문제를 확률적 (probabilistic)으로 해결하는 프로토콜 (protocol) [1]을 제안하고 악의적인 공격자 (malicious adversary) 모델과 다자간 계산으로 확장하였다. 이 논문에서는 기존의 프로토콜을 결정적 (deterministic) 방법으로 개선하여 Semi-Honest 모델에서 결과의 정확성을 보장하는 한편, 이를 악의적인 공격자 모델에 확장하여 신뢰도와 연산속도를 향상시키는 새로운 프로토콜을 제안한다.

• Communications of the Korean Mathematical Society
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• v.17 no.2
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• pp.321-330
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• 2002

Consider the random assignment (or bipartite matching) problem with iid uniform edge costs t(i, j). Let $A_{n}$ be the optimal assignment cost. Just recently does Aldous [2] give a rigorous proof that E $A_{n}$ longrightarrowζ(2). In this paper we establish the upper and lower bounds for Var $A_{n}$ , i.e., there exist two strictly positive but finite constants $C_1$ and $C_2$ such athat $C_1$ $n^{(-5}$2)/ (log n)$^{(-3}$2)/ $\leq$ Var $A_{n}$ $\leq$ $C_2$ $n^{-1}$ (log n)$^2$.EX>.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.2
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• pp.203-210
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• 2009

The problem of outdoor localization can be practically solved by GPS. However, GPS is not perfect and some areas of outdoor navigation should consider other solutions. This research deals with outdoor localization using an elevation map without GPS. This paper proposes a novel feature, elevation moment of inertia (EMOI), which represents the distribution of elevation as a function of distance from a robot in the elevation map. Each cell of an elevation map has its own EMOI, and outdoor localization can be performed by matching EMOIs obtained from the robot and the pre-given elevation map. The experiments and simulations show that the proposed EMOI can be usefully exploited for outdoor localization with an elevation map and this feature can be easily applied to other probabilistic approaches such as Markov localization method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.6
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• pp.75-83
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• 2007

A model based approach of tracking the limbs of a walking human subject is proposed in this paper. The tracking process begins by building a data base composed of conditional probabilities of motions between the limbs of a walking subject. With a suitable amount of video footage from various human subjects included in the database, a probabilistic model characterizing the relationships between motions of limbs is developed. The motion tracking of a test subject begins with identifying and tracking limbs from the surveillance video image using the edge and silhouette detection methods. When occlusion occurs in any of the limbs being tracked, the approach uses the probabilistic motion model in conjunction with the minimum cost based edge and silhouette tracking model to determine the motion of the limb occluded in the image. The method has shown promising results of tracking occluded limbs in the validation tests.

• International Journal of Control, Automation, and Systems
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• v.6 no.3
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• pp.413-423
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• 2008

The template matching method is used as a simple method to track objects or patterns that we want to search for in the input image data from image sensors. It recognizes a segment with the highest correlation as a target. The concept of this method is similar to that of SNF (Strongest Neighbor Filter) that regards the measurement with the highest signal intensity as target-originated among other measurements. The SNF assumes that the strongest neighbor (SN) measurement in the validation gate originates from the target of interest and the SNF utilizes the SN in the update step of a standard Kalman filter (SKF). The SNF is widely used along with the nearest neighbor filter (NNF), due to computational simplicity in spite of its inconsistency of handling the SN as if it is the true target. Probabilistic Strongest Neighbor Filter for m validated measurements (PSNF-m) accounts for the probability that the SN in the validation gate originates from the target while the SNF assumes at any time that the SN measurement is target-originated. It is known that the PSNF-m is superior to the SNF in performance at a cost of increased computational load. In this paper, we suggest an image tracking algorithm that combines the template matching and the PSNF-m to estimate the states of a tracked target. Computer simulation results are included to demonstrate the performance of the proposed algorithm in comparison with other algorithms.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.77-81
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• 2003

SDM (Structural Dynamics Modification) is a tool to improve dynamic characteristics of a structure, more specifically of a base structure, by adding or deleting auxiliary (modifying) structures. In this paper, the goal of the optimal SDM is set to maximize the natural frequency of a base plate structure by attaching serially-connected beam stiffeners. The design variables are chosen as positions of the attaching beam stiffeners, where the number of stiffeners is considered as a design space. The problem of non-matching interface nodes between the base plate and beam stiffeners is solved by using localized Lagrange multipliers, which act to glue the two structures with non-matching interface nodes. As fer the cases of non-matching interface nodes problem, the governing equation of motion of a structure can be considered from the viewpoint of a topological modification, which involves the change of the number of structural members and DOFs. Consequently, the eigenpairs of the beam-stiffened plate structure are obtained by using an eigen reanalysis technique of topological modifications. Evolution Strategies (ES), which is a probabilistic population-based optimization technique that mimics the principles from biological evolution in nature, is utilized as a mean for the optimization.

• Journal of Digital Convergence
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• v.10 no.2
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• pp.287-292
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• 2012

In this paper, user personalized services through the emotion perception required to support location-based sensing data preprocessing techniques and emotion data preprocessing techniques is studied for user's emotion data building and preprocessing in V-A emotion model. For this purpose the granular context tree and string matching based emotion pattern matching techniques are used. In addition, context-aware and personalized recommendation services technique using probabilistic reasoning is studied for personalized services based on context awareness.