• International Journal of Control, Automation, and Systems
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• v.2 no.2
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• pp.228-237
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• 2004

This paper provides a motion analysis of soft-fingertip object manipulation tasks by presenting a dynamic model of multi-fingered object manipulations with soft fingertips. It is fundamentally observed that soft fingertips employed in a multi-fingered hand generate some deformation effects during the manipulation process and also that those effects are closely related to the behavior of the manipulated object. In order to analyze the motion of using soft fingertips, a dynamic manipulation control scheme is presented. Simulation and experimental results demonstrate the motion of soft-fingertips applied in object manipulating tasks and are further used to discuss the characteristics of soft-fingertip motions.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.10
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• pp.194-202
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• 1999

A method for pattern recognition based on wavelet transform is proposed in this paper. The boundary of the object to be recognized includes shape information for object of machine parts. The contour is first represented using a one-dimensional signal and normalized about translation, rotation and scale, then is used to build the wavelet transform representation of the object. Wavelets allow us to decompose a function into multi-resolution hierarchy of localized frequency bands. The recognition of 2-dimensional object based on the wavelet is described to analyze the shape of analysis technique; the discrete wavelet transform(DWT). The feature vectors obtained using wavelet analysis is classified using a multi-layer neural network. The results show that, compared with the use of fourier descriptors, recognition using wavelet is more stable and efficient representation. And particularly the performance for objects corrupted with noise is better than that of other method.

• Journal of Broadcast Engineering
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• v.25 no.2
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• pp.192-199
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• 2020

Recently, the utilization of the object tracking algorithm based on the deep learning model is increasing. A system for tracking multiple objects in an image is typically composed of a chain form of an object detection algorithm and an object tracking algorithm. However, chain-type systems composed of several modules require a high performance computing environment and have limitations in their application to actual applications. In this paper, we propose a method that enables real-time operation in low-performance computing environment by adjusting the computational process of object detection module in the object detection-tracking chain type system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4976-4994
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• 2018

The diffusion-based salient object detection methods have shown excellent detection results and more efficient computation in recent years. However, the current diffusion-based salient object detection methods still have disadvantage of detecting the object appearing at the image boundaries and different scales. To address the above mentioned issues, this paper proposes a multi-scale diffusion-based salient object detection algorithm with background and objectness seeds. In specific, the image is firstly over-segmented at several scales. Secondly, the background and objectness saliency of each superpixel is then calculated and fused in each scale. Thirdly, manifold ranking method is chosen to propagate the Bayessian fusion of background and objectness saliency to the whole image. Finally, the pixel-level saliency map is constructed by weighted summation of saliency values under different scales. We evaluate our salient object detection algorithm with other 24 state-of-the-art methods on four public benchmark datasets, i.e., ASD, SED1, SED2 and SOD. The results show that the proposed method performs favorably against 24 state-of-the-art salient object detection approaches in term of popular measures of PR curve and F-measure. And the visual comparison results also show that our method highlights the salient objects more effectively.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.10
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• pp.958-964
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• 2015

In this paper, an object recognition method based on the depth information from the RGB-D camera, Xtion, is proposed for an indoor mobile robot. First, the RANdom SAmple Consensus (RANSAC) algorithm is applied to the point cloud obtained from the RGB-D camera to detect and remove the floor points. Next, the removed point cloud is classified by the k-means clustering method as each object's point cloud, and the normal vector of each point is obtained by using the k-d tree search. The obtained normal vectors are classified by the trained multi-layer perceptron as 18 classes and used as features for object recognition. To distinguish an object from another object, the similarity between them is measured by using Levenshtein distance. To verify the effectiveness and feasibility of the proposed object recognition method, the experiments are carried out with several similar boxes.

• Journal of the Semiconductor & Display Technology
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• v.14 no.3
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• pp.73-77
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• 2015

This paper proposes an object tracking system according to reliability assessment of learning in mobile environments. The proposed system is based on markerless tracking, and there are four modules which are recognition, tracking, detecting and learning module. Recognition module detects and identifies an object to be matched on current frame correspond to the database using LSH through SURF, and then this module generates a standard object information that has the best reliability of learning. The standard object information is used for evaluating and learning the object that is successful tracking in tracking module. Detecting module finds out the object based on having the best possible knowledge available among the learned objects information, when the system fails to track. The experimental results show that the proposed system is able to recognize and track the reliable objects with reliability assessment of learning for the use of mobile platform.

• Journal of the Korean Society for Railway
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• v.6 no.4
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• pp.221-231
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• 2003

Most rail system related simulators currently used are designed to simulate only one discipline system. This obviously assumes the other discipline systems are running regularly not being affected by the system being simulated. In this paper a multi discipline simulator is proposed and its design concept is presented. A multi discipline simulator is the simulator in which major subsystems with different technical discipline are simulated simultaneously. The advantage of the simulator is in that it makes it possible to analyze the systems behavior while other discipline system vary. With this we can identify the possible multi-discipline problems and even find their solutions. A proto type simulator has been developed using object oriented programming. Object concept was judged best suitable to model the various multi-discipline self-controlling railway subsystems. It was applied to the target system, which is under development by the Korea Railroad Research Institute. The test results shows it is very useful in designn verification. It could also be a good tool in research and development work to improve the system.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.1
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• pp.80-93
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• 2007

This paper suggests structures of the Object Descriptor and the Elementary Stream Descriptor that provide multi-view video services in 3-Dimensional Audio Video technical standards of current MPEG-4. First, it defines that the structures of the Object Descriptor and the Elementary Stream Descriptor on established MPEG-4 system, then distributes individually, and analyzes that. But extension of established system is inappropriate for providing multi-view audio video services connected transmissions and receptions. And, this paper suggests a structure of new Object Descriptor able to switch viewpoints that considers the correlation between each viewpoints, when multi-view video is transmitted. By means of that, it is able to switch viewpoints according to a requirement of a user in a multi-view video services, and reduce overheads for transmitting information about necessary viewpoint.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.4B no.4
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• pp.184-189
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• 2004

In this paper, multi-object optimization based on a progressive quadratic response surface method (PQRSM) and a time stepping finite element method (FEM) is proposed. The new PQRSM and FEM are able to decide optimal geometric and electric variables of the switched reluctance motor (SRM) with two objective functions: torque ripple minimization and average torque maximization. The result of the optimum design for SRM demonstrates improved performance of the motor and enhanced relationship between torque ripple and average torque.

• Language and Information
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• v.19 no.1
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• pp.1-18
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• 2015

Korean marks case for subjects and objects, but it is well known that case-markers can be dropped in certain contexts. Kwon and Zribi-Hertz (2008) establishes the phenomenon of Korean case drop on a single factor of f(ocus)-structure visibility and claims that both subject and object case drop can fall under a single linguistic generalization of information structure. However, the supporting data is not empirically substantiated and the tenability of the f-structure analysis is still under question. In this paper, an experiment was conducted to show that the specific claims of Kwon and Zribi-Hertz's analysis that places exclusive importance on information structure cannot be adequately supported by empirical evidence. In addition, the present study examines H. Lee's (2006a, 2006c) multi-factor analysis of object case drop and investigates whether this approach can subsume both subject and object case drop under a unified analysis. The present findings indicate that the multi-factor analysis that involves the interaction of independent factors (Focus, Animacy, and Definiteness) is also compatible with subject case drop, and that judgments on case drop are not categorical but form gradient statistical preferences.