• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.661-665
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• 1996

An inverse kinemetics problem of a reclaimer which digs and transports ironstones or coals in the raw yard is investigated. Because of the special features of the reclaimer of which scooping buckets are attached around the rotating drum at the end of boom, kinematic redundancy occurs in determining the joint varialbes For a given reclaiming point in space the forward kinematics yields 3 equations, however the number of involved variables in the equations are four. A plane equation approximating the surface near a reclaiming point is obtained by considering 8 adjacent points surrounding the reclaiming point. One extra equation to overcome redunduncyis further obtained from the condition that the normal vector at a reclaiming point is perpendicular to the plane. An approximate solution for a simplified problem is first discussed, Numerical solution for the oritinal nonlinear porblem with a constraint equation is also investigated. Finally a closed form solution which is not exact but sufficiently close enough is proposed by exploiting geometric constraint.

• The Journal of Korea Robotics Society
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• v.3 no.2
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• pp.106-111
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• 2008

This paper presents a decentralized coordination for a small-scale mobile robot teams performing a task through cooperation. Robot teams are required to generate and maintain various geometric patterns adapting to an environment and/or a task in many cooperative applications. In particular, all robots must continue to strive toward achieving the team's mission even if some members fail to perform their role. Toward this end, given the number of robots in a team, an effective coordination is investigated for decentralized formation control strategies. Specifically, all members are required first to reach agreement on their coordinate system and have an identifier (ID) for role assignment in a self-organizing way. Then, employing IDs on individual robots within a common coordinate system, a decentralized neighbor-referenced formation control is realized to generate, keep, and switch between different geometric shapes. This approach is verified using an in-house simulator and physical mobile robots. We detail and evaluate the formation control approach, whose common features include self-organization, robustness, and flexibility.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.1
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• pp.105-113
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• 2010

SAR(Synthetic Aperture Radar) has characteristics well-suited for the measurement of geophysical parameters during day and night in all weather conditions. Recently, SAR data with high resolution acquired by satellites became available to the public. In such data, many features and phenomena of geometric structure of man-made objects and natural environments become observable. In this paper, we discuss main considerations including geometric distortion and coregistration for efficient utilization of high resolution SAR images. And, various advanced technologies in SAR application fields are introduced.

• IE interfaces
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• v.13 no.4
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• pp.703-708
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• 2000

In manufacturing processes, manufacturing features always deviate somewhat from their nominal design specifications due to several types of errors. This study suggests a fitting algorithm of the geometric profile parameters of leading and trailing edges for turbine compressor airfoils. In reality, industry personnels inspect the airfoil profile by trial-and-error method to determine the geometric feature parameters. In this study we propose an exploration approach based on factorial design with center point to minimize the effect of measurement errors caused by probe slip. By adopting the fitting method developed in this paper, one can enhance the precision and efficiency of fitting the airfoil edge profile.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.5
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• pp.355-369
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• 2018

LiDAR (Light Detection And Ranging) strip adjustment is process to improve geo-referencing of the ALS (Airborne Laser Scanner) strips that leads to seamless LiDAR data. Multiple strips are required to collect data over the large areas, thus the strips are overlapped in order to ensure data continuity. The LSA (LiDAR Strip Adjustment) consists of identifying corresponding features and minimizing discrepancies in the overlapping strips. The corresponding features are utilized as control features to estimate transformation parameters. This paper applied SURF (Speeded Up Robust Feature) to identify corresponding features. To improve determination of the corresponding feature, false matching points were removed by applying three schemes: (1) minimizing distance of the SURF feature vectors, (2) selecting reliable matching feature with high cross-correlation, and (3) reflecting geometric characteristics of the matching pattern. In the strip adjustment procedure, corresponding points having large residuals were removed iteratively that could achieve improvement of accuracy of the LSA eventually. Only a few iterations were required to reach reasonably high accuracy. The experiments with simulated and real data show that the proposed method is practical and effective to airborne LSA. At least 80 % accuracy improvement was achieved in terms of RMSE (Root Mean Square Error) after applying the proposed schemes.

• The Journal of Korea Robotics Society
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• v.8 no.4
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• pp.266-272
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• 2013

Facial feature extraction and tracking are essential steps in human-robot-interaction (HRI) field such as face recognition, gaze estimation, and emotion recognition. Active shape model (ASM) is one of the successful generative models that extract the facial features. However, applying only ASM is not adequate for modeling a face in actual applications, because positions of facial features are unstably extracted due to limitation of the number of iterations in the ASM fitting algorithm. The unaccurate positions of facial features decrease the performance of the emotion recognition. In this paper, we propose real-time facial feature extraction and tracking framework using ASM and LK optical flow for emotion recognition. LK optical flow is desirable to estimate time-varying geometric parameters in sequential face images. In addition, we introduce a straightforward method to avoid tracking failure caused by partial occlusions that can be a serious problem for tracking based algorithm. Emotion recognition experiments with k-NN and SVM classifier shows over 95% classification accuracy for three emotions: "joy", "anger", and "disgust".

• Korean Journal of Computational Design and Engineering
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• v.16 no.3
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• pp.178-186
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• 2011

Static CAD models are the CAD models that do not have feature information and modeling history. These static models are generated by translating CAD models in a specific CAD system into neutral formats such as STEP and IGES. When a CAD model is translated into a neutral format, its precious feature information such as feature parameters and modeling history is lost. Once the feature information is lost, the advantage of feature based modeling is not valid any longer, and modification for the model is purely dependent on geometric and topological manipulations. However, the capabilities of the existing methods to modify static CAD models are limited, Direct modification methods such as tweaking can only handle the modifications that do not involve topological changes. There was also an approach to modify static CAD model by using volume decomposition. However, this approach was also limited to modifications of protrusion features. To address this problem, we extend the volume decomposition approach to handle not only protrusion features but also depression features in a static CAD model. This method first generates the model that contains the volume of depression feature using the bounding box of a static CAD model. The difference between the model and the bounding box is selectively decomposed into so called the feature volume and the base volume. A modification of depression feature is achieved by manipulating the feature volume of the static CAD model.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.7
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• pp.685-692
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• 2016

In this paper, we not only take advantage of the SIFT features in banknote recognition, which has robustness to illumination changes, geometric rotation as well as scale changes, but also propose the hierarchical banknote recognition algorithm, which comprised of feature vector extraction from the frame grabbed image of the banknotes, and matching to the prepared data base of multinational banknotes by ANN algorithm. The images of banknote under the developed UV, IR and white illumination are used so as to extract the SIFT features peculiar to each banknotes. These SIFT features are used in recognition of the nationality as well as face value. We confirmed successful function of the proposed algorithm by applying the proposed algorithm to the banknotes of Korean and USD as well as EURO.

• Convergence Security Journal
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• v.14 no.5
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• pp.49-56
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• 2014

In this paper, we proposed a method for representing local facial features based on LDP (Local Directional Pattern). To represent both PFF (Permanent Facial Features) and TFF (Transient Facial Features) effectively, the proposed method configure local facial feature vectors based on overlapped blocks for each facial feature in the forms of various size and shape. There are three advantages - it take advantages of geometric feature based method; it shows robustness about detection error using movement characteristics of each facial feature; and it shows reduced sampling error because maintain spatial information caused by block size variability. Proposed method shows better classification accuracy and reduced amount of calculation than existing methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.4300-4314
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• 2019

With the development of video-related applications, media content has increased dramatically through applications. There is a substantial amount of near-duplicate videos (NDVs) among Internet videos, thus NDVR is important for eliminating near-duplicates from web video searches. This paper proposes a novel NDVR system that supports large-scale retrieval and contributes to the efficient and accurate retrieval performance. For this, we extracted keyframes from each video at regular intervals and then extracted both commonly used features (LBP and HSV) and new image features from each keyframe. A recent study introduced a new image feature that can provide more robust information than existing features even if there are geometric changes to and complex editing of images. We convert a vector set that consists of the extracted features to binary code through a set of hash functions so that the similarity comparison can be more efficient as similar videos are more likely to map into the same buckets. Lastly, we calculate similarity to search for NDVs; we examine the effectiveness of the NDVR system and compare this against previous NDVR systems using the public video collections CC_WEB_VIDEO. The proposed NDVR system's performance is very promising compared to previous NDVR systems.