• International Journal of Control, Automation, and Systems
• /
• 제2권2호
• /
• pp.228-237
• /
• 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.

• 한국정밀공학회지
• /
• 제16권10호
• /
• pp.194-202
• /
• 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.

• 방송공학회논문지
• /
• 제25권2호
• /
• pp.192-199
• /
• 2020

최근 딥러닝 모델을 기반으로 한 객체 추적 알고리즘의 활용도가 증가하고 있다. 영상에서의 다중 객체의 추적을 위한 시스템은 대표적으로 객체 검출 알고리즘과 객체 추적 알고리즘의 연쇄된 형태로 구성되어있다. 하지만 여러 모듈로 구성된 연쇄 형태의 시스템은 고성능 컴퓨팅 환경을 요구하며 실제 어플리케이션으로의 적용에 제한사항으로 존재한다. 본 논문에서는 위와 같은 객체 검출-추적의 연쇄 형태의 시스템에서 객체 검출 모듈의 연산 관련 프로세스를 조정하여 저성능 컴퓨팅 환경에서도 실시간 동작을 가능하게 하는 방법을 제안한다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제12권10호
• /
• pp.4976-4994
• /
• 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.

• 제어로봇시스템학회논문지
• /
• 제21권10호
• /
• pp.958-964
• /
• 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.

• 반도체디스플레이기술학회지
• /
• 제14권3호
• /
• pp.73-77
• /
• 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.

• 한국철도학회논문집
• /
• 제6권4호
• /
• pp.221-231
• /
• 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.

• 전자공학회논문지CI
• /
• 제44권1호
• /
• pp.80-93
• /
• 2007

본 논문은 현재 MPEG-4의 3차원 오디오/비디오(3-Dimensional Audio Video, 3DAV) 기술표준에서 다시점 비디오(Multi-view video)서비스를 제공할 수 있는 객체기술자(Object Descriptor)와 기초스트림기술자(Elementary Stream Descriptor)의 구조를 제안한다. 기존의 MPEG-4 시스템 상에서 확장영역을 사용하여 다시점 동영상 서비스를 제공 할 수 있는 객체기술자와 기초스트림의 구조를 각각 정의 하여 분류한 후 각 경우에 대해 분석한다. 기존 시스템의 확장만으로 송수신측과 연계되어 상관관계가 고려된 다시점 비디오 서비스 제공하는 것이 부적합하다는 것을 보인다. 그리고 다시점 영상 전송시 수신측에서 각 시점간의 상관관계를 고려하여 시점 스위칭을 할 수 있는 새로운 객체 기술자를 추가한 구조를 제안한다. 이를 통하여 다시점 비디오 서비스에서 사용자 요구에 따른 시점 전환을 가능하게 하면서, 필요한 시점에 대한 정보만을 전송해서 수신측에 부하를 줄일 수 있다.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
• /
• 제4B권4호
• /
• pp.184-189
• /
• 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.

• 한국언어정보학회지:언어와정보
• /
• 제19권1호
• /
• pp.1-18
• /
• 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.