• Journal of Institute of Control, Robotics and Systems
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• v.22 no.1
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• pp.8-16
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• 2016

In the field of computer vision and robotics, bin picking is an important application area in which object pose estimation is necessary. Different approaches, such as 2D feature tracking and 3D surface reconstruction, have been introduced to estimate the object pose accurately. We propose a new approach where we can use both 2D image features and 3D surface information to identify the target object and estimate its pose accurately. First, we introduce a label detection technique using Maximally Stable Extremal Regions (MSERs) where the label detection results are used to identify the target objects separately. Then, the 2D image features on the detected label areas are utilized to generate 3D surface information. Finally, we calculate the 3D position and the orientation of the target objects using the information of the 3D surface.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.2
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• pp.47-55
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• 2023

Recently, Sensor technologies are emerging to prevent traffic accidents and support safe driving in complex environments where human perception may be limited. The UWS is a technology that uses an ultrasonic sensor to detect objects at short distances. While it has the advantage of being simple to use, it also has the disadvantage of having a limited detection distance. The LDWS, on the other hand, is a technology that uses front image processing to detect lane departure and ensure the safety of the driving path. However, it may not be sufficient for determining the driving environment around the vehicle. To overcome these limitations, a system that utilizes FMCW radar is being used. The BSD radar system using FMCW continuously emits signals while driving, and the emitted signals bounce off nearby objects and return to the radar. The key technologies involved in designing the BSD radar system are tracking algorithms for detecting the surrounding situation of the vehicle. This paper presents a tracking algorithm for designing a BSD radar system, while explaining the principles of FMCW radar technology and signal types. Additionally, this paper presents the target tracking procedure and target filter to design an accurate tracking system and performance is verified through simulation.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.35 no.3
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• pp.237-241
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• 1999

It was investigated that the condition of fishing ground gave what kind of effect school type in relation to the property for the target school after the vertical temperature profile and school type were observed when tuna purse seiner for tuna purse seine was operated in the western pacific Ocean around the equator between December 12, 1993 and January 26, 1994. The results are as follows;1. This study divided fish schools associated with drift objects, a one targeted-operation, and the pelagic migrating fish schools that are another one for the property. The total of 23 operations were complected including 6 that targeted fish schools associated with drift objects and 17 that targeted pelagic migrating fish schools. It was known that the main operation was conducted on pelagic migrating fish school.2. Average and standard deviation of the depth of the surface mixing layer was 86.0m and 13.8m for fish schools associated with drift objects. 61.6m and 13.0m for pelagic migrating fish schools, respectively. The average depth of the surface mixing layer of the pelagic migrating fish schools was lower when compared to the fish schools associated with drift objects however the concentration of standard deviation was higher than those fish schools associated with drifted objects. Accordingly, it was assumed that the effect of vertical temperature profile for pelagic migrating fish school was higher than the fish schools associated with drift objects.

• Journal of KIISE:Databases
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• v.35 no.2
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• pp.182-191
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• 2008

Most of previous works for skyline queries have focused only on static attributes of target objects. With the advance in mobile applications, however, the need of continuous skyline queries for moving objects has been increasing. Even though several techniques to process continuous skyline queries have been proposed recently, they cannot process subspace queries, which use only the subset of attribute dimensions. Therefore it is not feasible to utilize those methods for mobile applications which must consider moving objects and subspaces simultaneously. In this paper, we propose a dominant object-based pruning method to compute subspace skyline of moving objects efficiently at query time and present the experimental results to show the effectiveness of the proposed method.

• The Journal of Korea Robotics Society
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• v.16 no.4
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• pp.299-305
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• 2021

In this study, the task of robotic tidy-up is to clean the current environment up exactly like a target image. To perform a tidy-up task using a robot, it is necessary to estimate the pose of various objects and to classify the objects. Pose estimation requires the CAD model of an object, but these models of most objects in daily life are not available. Therefore, this study proposes an algorithm that uses point cloud and PCA to estimate the pose of objects without the help of CAD models in cluttered environments. In addition, objects are usually detected using a deep learning-based object detection. However, this method has a limitation in that only the learned objects can be recognized, and it may take a long time to learn. This study proposes an image matching based on few-shot learning and Siamese network. It was shown from experiments that the proposed method can be effectively applied to the robotic tidy-up system, which showed a success rate of 85% in the tidy-up task.

• The Bulletin of The Korean Astronomical Society
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• v.35 no.2
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• pp.26-26
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• 2010

Gravitationally bound objects in the universe have been a main target of astronomers for long. However, some objects in the universe may want to be free, as we do. Recently we are witnessing the existence of some globular clusters wandering in the nearby universe. The nature and origin of these wandering globular clusters are not yet known. With the advent of giant telescopes they will be an excellent tool for various fields of research including first stars, star clusters, galaxies, and galaxy clusters.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.8B
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• pp.1424-1435
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• 2000

A bit-rate controller that can achieve a constant bit rate when coding object-based video sequences is an important part to achieve an adaptation to bit-rate constraints, desired video quality, distribution of bits among objects, relationship between texture and shape coding, and determination of frame skip or not. Therefore we design content-based bit rate controller which will be used for relevant bit-rate control. The implementation is an extension of MPEG-4 rate control algorithm which employs a quadratic rate-quantizer model. The importance of different objects in a video is analyzed and segmented into a number of VOPs which are adaptively bit-allocated using the object-based modelling. Some test sequences are observed by a number of non-experts and interests in each object are analysed. The initial total target bit-rate for all objects is obtained by using the proposed technique. Then the total target bits are jointly analyzed for preventing from overflow or underflow of the buffer fullness. The target bits are distributed to each object in view of its importance, not only of statistical analysis such as motion vector magnitude, size of object shape, and coding distortion of previous frame. The scheme is compared with the rate controller adopted by the MPEG-4 VM8 video coder by representing their statistics and performance.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.4
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• pp.159-168
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• 2018

In recent, mobile augmented reality game which has been attracting high attention is considered to be an good approach to increase immersion. In conventional augmented reality-based games that recognize target objects using a mobile camera and show the matching game characters, touch-based interaction is mainly used. In this paper, we propose an intuitive interaction method which manipulates a deformable game object by moving a target image of augmented reality in order to enhacne the immersion of the game. In the proposed method, the deformable object is intuitively manipulated by calculating the distance and direction between the target images and by adjusting the external force applied to the deformable object using them. In this paper, we focus on the cloth deformable object which is widely used for natural object animation in game contents and implement natural cloth simulation interacting with game objects represented by wind and rigid objects. In the experiments, we compare the previous commercial cloth model with the proposed method and show the proposed method can represent cloth animation more realistically.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4929-4947
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• 2017

In visual object tracking, Correlation Filter-based Tracking (CFT) systems have arouse recently to be the most accurate and efficient methods. The CFT's circularly shifts the larger search window to find most likely position of the target. The need of larger search window to cover both background and object make an algorithm sensitive to the background and the target occlusions. Further, the use of fixed-sized windows for training makes them incapable to handle scale variations during tracking. To address these problems, we propose two layer target representation in which both global and local appearances of the target is considered. Multiple local patches in the local layer provide robustness to the background changes and the target occlusion. The target representation is enhanced by employing additional reversed RGB channels to prevent the loss of black objects in background during tracking. The final target position is obtained by the adaptive weighted average of confidence maps from global and local layers. Furthermore, the target scale variation in tracking is handled by the statistical model, which is governed by adaptive constraints to ensure reliability and accuracy in scale estimation. The proposed structural enhancement is tested on VTBv1.0 benchmark for its accuracy and robustness.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1973-1974
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• 2006

The mean shift algorithm has achieved considerable success in object tracking due to its simplicity and robustness. It finds local maxima of a similarity measure between the color histograms of the target and candidate image. However, the mean shift tracking algorithm using only color histograms has a serious defect. It doesn't use the spatial information of the target. Thus, it is difficult to model the target more exactly. And it is likely to lose the target during the occlusions of other objects which have similar color distributions. To deal with these difficulties we use both color information and spatial information of the target. Our proposed algorithm is robust to occlusions and scale changes in front of dynamic, unstructured background. In addition, our proposed method is computationally efficient. Therefore, it can be executed in real-time.