• KIPS Transactions on Software and Data Engineering
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• v.6 no.1
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• pp.9-14
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• 2017

Embedded devices with the development of modern computer technology also began equipped with a variety of functions. In this study, to provide a method of tracking efficient face with a small instrument of resources, such as built-in equipment that uses an image sensor in recent years has been actively carried out. It uses a face detection method using the features of the MB-LBP in order to obtain an accurate face, specify the region (Region of Interest) around the face when the face detection for the face object tracking in the next video did. And in the video can not be detected faces, to track objects using the CAM-Shift key is a conventional object tracking method, which make it possible to retain the information without loss of object information. In this study, through the comparison with the previous studies, it was confirmed the precision and high-speed performance of the object tracking system.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.2
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• pp.124-132
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• 2005

We propose a method using a transformation of an object and a scene tree in order to author MPEG-4 contents for mobile devices in this paper. The method transforms media objects in the scene into geometry objects in order to reduce initial loading time of the contents, and reduces an external form of each object in a scene of the content for presenting it efficiently on the small interface of mobile devices. Therefore, the contents for mobile devices are reconstructed by the method. An original object in the scene is presented on a mobile device when a user clicks a related geometry object. The method was applied to a conventional authoring tool, so we could find that the method showed an efficient presentation of MPEG-4 contents on mobile devices.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.186-192
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• 2021

Recently, the demand for more precise and demand-oriented customized spatial information is increasing due to the 4th industrial revolution. In particular, the use of 3D spatial information and digital twins which based on spatial information, and research for solving social problems in cities by using such information are continuously conducted. Globally, non-face-to-face services are increasing due to COVID-19, and the national policy direction is also rapidly progressing digital transformation, digitization and virtualization of the Korean version of the New Deal, which means that 3D spatial information has become an important factor to support it. In this study, physical objects for cities defined by world organizations such as ISO, OGC, and ITU were selected and the target of the 3D object model was limited to buildings. Based on CityGML2.0, the data collected using a drone suitable for building a 3D model of a small area is selected to be updated through road name address and building ledger, which are administrative information related to this, and LoD2.5 data is constructed and urban space. It was intended to suggest an object update method for a 3D building among data.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.5
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• pp.203-208
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• 2023

Recently, with the growing interest in the field of autonomous driving, many researchers have been focusing on developing autonomous driving software platforms. In particular, we have concentrated on developing 3D object detection models that can improve real-time performance. In this paper, we introduce a self-constructed 3D LiDAR dataset specific to domestic environments and propose a VariFocal-based CenterPoint for the 3D object detection model, with improved performance over the previous models. Furthermore, we present experimental results comparing the performance of the 3D object detection modules using our self-built and public dataset. As the results show, our model, which was trained on a large amount of self-constructed dataset, successfully solves the issue of failing to detect large vehicles and small objects such as motorcycles and pedestrians, which the previous models had difficulty detecting. Consequently, the proposed model shows a performance improvement of about 1.0 mAP over the previous model.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.1
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• pp.1-8
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• 2024

Robotic arms have been widely utilized in various labor-intensive industries such as manufacturing, agriculture, and food services, contributing to increasing productivity. In the development of industrial robotic arms, camera sensors have many advantages due to their cost-effectiveness and small sizes. However, estimating object positions is a challenging problem, and it critically affects to the robustness of object manipulation functions. This paper proposes a method for estimating the 3D positions of objects, and it is applied to a pick-and-place task. A deep learning model is utilized to detect 2D bounding boxes in the image plane, and the pinhole camera model is employed to compute the object positions. To improve the robustness of measuring the 3D positions of objects, we analyze the effect of lens distortion and introduce a false positive filtering process. Experiments were conducted on a real-world scenario for moving medicine bottles by using a camera-based manipulator. Experimental results demonstrated that the distortion removal and false positive filtering are effective to improve the position estimation precision and the manipulation success rate.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.2
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• pp.119-126
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• 2017

Developing the TCP/IP standard IBA which is higher organization of IETF decided to attach the TCP/IP protocol stack to small things, such as sensor. This means small object is also considered as on of the communication node, it has symbolic meaning that expand smart object has all five layer. Under this background, IoT/WoT configure the intelligent network between objects based on the internet to communication was introduced. Things has own IP address on IoT environment and are smart object that a lot of people communicate over the internet on Application Layer. In other words, IoT is that smart object are commercialized space. According to the interest of IoT, IETF establish CoAP for use as IoT protocol. CoAP is expected that standard protocols created by things is connected to the Internet protocol that can be used within a constrained environment. Accordingly, in this paper, we proposed Middleware API that can manage and collect the data of objects that connected CoAP network.

• Journal of the Korea Computer Graphics Society
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• v.21 no.4
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• pp.19-26
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• 2015

This paper presents a method for optimizing a carrying pose of human body for a given object. The inputs are articulated human body model and and arbitrary-shaped object. We assume that the object is big and heavy, so that both arms should be used to carry it. Unlike small and light objects, big and heaby objects can be hold by only a small range of body poses while keeping a physical statbility. We first introduce an algorithm that evaluates a physical stability of a given human body pose and object state (position and orientation). Then, we define a configuration space and search the space for the most stable carrying pose by using the evaluation algorithm. Finally, to demonstrate the usability of our method, we present the results which each is experimented with different shaped objects and additional user conditions.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.177-198
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• 2021

Existing change detection researches have been focused on changes of land use and land cover (LULC), damaged areas, or large vegetated and water regions. On the other hands, increased temporal and spatial resolution of satellite images are strongly suggesting the feasibility of change detection of small objects such as vehicles and ships. In order to check the feasibility, this paper analyzes the performance of existing pixel-based change detection methods over small objects. We applied pixel differencing, PCA (principal component analysis) analysis, MAD (Multivariate Alteration Detection), and IR-MAD (Iteratively Reweighted-MAD) to Kompsat-3A and Google Map images taken within 10 days. We extracted ground references for changed and non-changed small objects from the images and used them for performance analysis of change detection results. Our analysis showed that MAD and IR-MAD, that are known to perform best over LULC and large areal changes, offered best performance over small object changes among the methods tested. It also showed that the spectral band with high reflectivity of the object of interest needs to be included for change analysis.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.7 no.2
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• pp.82-85
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• 2014

It is helpful to use Intelligent Video Surveillance to replace and supplement the demerit which can possibly occur due to the mistake that can be made by human management. To accomplish this, it is essential that the system should digitalize image information from surveillance camera so that the system, itself, can be able to locate a object and to analyze the pattern of the object. Also, it is imperative that the system should have ability to operate a alarm and a entrance blocking system and to notify a situation to a security manager. Zooming a small object form a screen, however, requires a exact zooming ratio of the object and a shift of centric coordinate. In this paper, It is able to locate and observe closely a object from flexible background, regardless of the distance, by calculating a zooming ratio according to object moment, pan coordinate, and tilt coordinate.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.2
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• pp.364-370
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• 2011

This paper propose a novel method for tracking moving object based on covariance matrix and Riemannian Manifolds. With image backgrounds continuously changed, we use the covariance matrices to extract features for tracking nonrigid object undergoing transformation and deformation. The covariance matrix can make fusion of different types of features and has its small dimension, therefore we enable to handle the spatial and statistical properties as well as the component correlation. The proposed method can estimate the position of the moving object by employing the covariance matrix of object region as a feature vector and comparing the candidate regions. Rimannian Geometry is efficiently adapted to object deformation and change of shape and improve the accuracy by using geodesic distance to predict the estimated position with the minimum distance. The experimental results have shown that the proposed method correctly tracked the moving object.