• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.5
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• pp.1400-1420
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• 2012

Object detection and tracking using visual sensors is a critical component of surveillance systems, which presents many challenges. This paper addresses the enhancement of object detection and tracking via the combination of multiple visual sensors. The enhancement method we introduce compensates for missed object detection based on the partial detection of objects by multiple visual sensors. When one detects an object or more visual sensors, the detected object's local positions transformed into a global object position. Local and global information exchange allows a missed local object's position to recover. However, the exchange of the information may degrade the detection and tracking performance by incorrectly recovering the local object position, which propagated by false object detection. Furthermore, local object positions corresponding to an identical object can transformed into nonequivalent global object positions because of detection uncertainty such as shadows or other artifacts. We improved the performance by preventing the propagation of false object detection. In addition, we present an evaluation method for the final global object position. The proposed method analyzed and evaluated using case studies.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.53-56
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• 2000

In progressive image coding, if object region that have main contents in image are transmitted prior to the remained region, this method will be very useful. In this paper, the progressive image coding based on SPIHT using object region transmission method by priority is proposed. First, an original image is transformed by wavelet. Median filtering is used about wavelet transformed coefficient region for extracting object region. This extracted object region encoded by SPIHT. Then encoded object region are transmitted in advance of the remained region. This method is good to a conventional progressive image coding about entire original image. Experimental results show that the proposed method can be very effectively used for image coding applications such as internet retrieval and database searching system.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.221-225
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• 1998

This paper is to present a method for recognizing an image of a tracking object by processing the image from a camera, whose attitude is controlled in inertial space with inertial co-ordinate system. In order to recognize an object, a pseudo-random M-array is attached on the object and it is observed by the camera which is controlled on inertial coordinate basis by inertial stabilization unit. When the attitude of the camera is changed, the observed image of M-array is transformed by use of affine transformation to the image in inertial coordinate system. Taking the cross-correlation function between the affine-transformed image and the original image, we can recognize the object. As parameters of the attitude of the camera, we used the azimuth angle of camera, which is de-fected by gyroscope of an inertial sensor, and elevation an91e of camera which is calculated from the gravitational acceleration detected by servo accelerometer.

• Journal of the Korea Society of Computer and Information
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• v.16 no.11
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• pp.25-34
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• 2011

In this paper we present an integrated design methodology for relational database based on object-oriented analysis and design. The integrated design methodology is based on business profile and has six phases. In the first phase, business use cases are identified and described by macroactivity diagrams and then the macroactivity diagrams are transformed to detailed business activity diagrams by using objects, object flows and business worker's responsibilities. In the third phase, the detailed business activity diagrams are transformed to business class diagrams that describe the static structure of the entire business system based on detailed business activity diagrams. In the four phase, the business class diagrams are transformed to class diagrams that represent the initial conceptual model of the target relational database. In the five phase, we add additional transformations on the class diagrams with generalization and specialization of associations, roles, activities, additional classes and redundant associations. Eventually, the final class diagrams are transformed to relational database schema. The methodology presented in this paper by applying that proposal for organic connection between object-oriented analysis and design methodology and relational database design methodology. And it will be able to deal with integration management. By the integrated design methodology, we can make more easily software systems based on relational database. In the case study, proposal integrated design methodology applied for a visa issuing system.

• Journal of Digital Convergence
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• v.19 no.4
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• pp.227-233
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• 2021

Ready-made products produced in the industrialized consumer society after the 20th century have been adopted by artists as a new material called "Found object," and are reinterpreted in a broad sense in their works. The method of giving new meaning using this creates a new paradigm that is expanded conceptually as well as expression style. After Pablo Picasso's in 1912, when the Found object was used for the first time in contemporary art, we examine the development of objects through Dadaism, Surrealism, and Pop Art, and the expression of Found objects in the late 20th century. In this study, the artists and their work are analyzed by dividing it into three types: 'Unprocessed objects', 'Transformed objects', and 'Tenant objects', depending on how the Found object is mixed in works. Through this study, I pay attention to the fact that a work incorporating a Found object not only develops the object materially, but also allows the practice of free concept art to escape from the traditional norms of art.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.10a
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• pp.211-218
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• 2002

An entity-based integrated design product and process model uses product and process entities to describe design information and design activities, respectively. The concepts and notation for product and process entities in the entity-based integrated design model are similar to the concepts of object-oriented programming languages such as C++ and Smalltalk. This paper uses C++ to program an entity-based integrated design model for building frames structures. The design information and activities involved in the three dimensional building space, the locations of frames, and the grouping of frames represented as entities in the entity-based integrated design model are transformed to C++ codes. Each product or process entity can be basically transformed to an class. The attributes of an entity can be defined as variables and member functions of a class.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.8
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• pp.119-128
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• 1994

In this paper we propose a new method for the recognition of 2-D partially occluded objects. The border of the object is transformed to a curve in arc length-accumulated interior angle plane. The transformed curve of an image is partitioned so that each segment is bounded by the concave interior angles. In order to tolerate shape distortion due to the polygonal approximation of the boundary of the object a group of feature points of the input image are matched with those of model views. The estimation method for positions and orientations of the identified objects objects is presented.

• Proceedings of the Korean Printing Society Conference
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• 2000.04a
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• pp.35-44
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• 2000

Because Image on the CRT change under different illuminants, human is difficult to see original color of object. If what is information of used illuminant on capturing object know, image can be transformed according to viewing condition using the linear matrix method. To know information of used illuminant at an image, the spectral radiance of illuminant can be estimated using the linear model of Maloney and Wandell form an image. And then image can be properly transformed it using color appearance model. In this paper, we predict the spectral radiance of illuminant using spectral power distribution of specular light and using surface spectral reflectance at maximum gray area. and then we perform visual experiments for the corresponding color reproduction according to viewing condition. In results, we ensure that the spectral radiance of illuminant at an image can be well estimated using above algorithms and that human visual system is 70% adapted to the monitor's white point and 30% to ambient light when viewing softcopy images.

• The Journal of Korea Robotics Society
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• v.13 no.1
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• pp.1-7
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• 2018

The image-to-image translation is one of the deep learning applications using image data. In this paper, we aim at improving the performance of object transfiguration which transforms a specific object in an image into another specific object. For object transfiguration, it is required to transform only the target object and maintain background images. In the existing results, however, it is observed that other parts in the image are also transformed. In this paper, we have focused on the structure of artificial neural networks that are frequently used in the existing methods and have improved the performance by adding constraints to the exiting structure. We also propose the advanced structure that combines the existing structures to maintain their advantages and complement their drawbacks. The effectiveness of the proposed methods are shown in experimental results.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.7-13
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• 2021

This paper presents an vulnerable road user (VRU) classification and tracking algorithm using vision and LiDAR sensor fusion method for urban autonomous driving. The classification and tracking for vulnerable road users such as pedestrian, bicycle, and motorcycle are essential for autonomous driving in complex urban environments. In this paper, a real-time object image detection algorithm called Yolo and object tracking algorithm from LiDAR point cloud are fused in the high level. The proposed algorithm consists of four parts. First, the object bounding boxes on the pixel coordinate, which is obtained from YOLO, are transformed into the local coordinate of subject vehicle using the homography matrix. Second, a LiDAR point cloud is clustered based on Euclidean distance and the clusters are associated using GNN. In addition, the states of clusters including position, heading angle, velocity and acceleration information are estimated using geometric model free approach (GMFA) in real-time. Finally, the each LiDAR track is matched with a vision track using angle information of transformed vision track and assigned a classification id. The proposed fusion algorithm is evaluated via real vehicle test in the urban environment.