• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.247-256
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• 2022

Visual tracking of selected target objects is fundamental challenging problems in computer vision. Object tracking localize the region of target object with bounding box in the video. We propose a Siam-FPN based custom fully CNN to solve visual tracking problems by regressing the target area in an end-to-end manner. A method of preserving the feature information flow using a feature map connection structure was applied. In this way, information is preserved and emphasized across the network. To regress object region and to classify object, the region proposal network was connected with the Siamese network. The performance of the tracking algorithm was evaluated using the OTB-100 dataset. Success Plot and Precision Plot were used as evaluation matrix. As a result of the experiment, 0.621 in Success Plot and 0.838 in Precision Plot were achieved.

• Journal of Korea Multimedia Society
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• v.17 no.5
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• pp.556-565
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• 2014

This paper proposes a method to track object of real-time video transferred through single web-camera and to recognize risk-situation and human actions. The proposed method recognizes human basic actions that human can do in daily life and finds risk-situation such as faint and falling down to classify usual action and risk-situation. The proposed method models the background, obtains the difference image between input image and the modeled background image, extracts human object from input image, tracts object's motion and recognizes human actions. Tracking object uses the moment information of extracting object and the characteristic of object's recognition is moment's change and ratio of object's size between frames. Actions classified are four actions of walking, waling diagonally, sitting down, standing up among the most actions human do in daily life and suddenly falling down is classified into risk-situation. To test the proposed method, we applied it for eight participants from a video of a web-cam, classify human action and recognize risk-situation. The test result showed more than 97 percent recognition rate for each action and 100 percent recognition rate for risk-situation by the proposed method.

• Journal of Korea Multimedia Society
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• v.9 no.4
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• pp.490-504
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• 2006

It needs to control each objects on various platform and transmit multimedia data to multiple receivers which are for developing a multimedia service with multimedia live streaming in a distributed environment. In this paper, we present a DLS (Distributed Live Streaming) package which support l:N multimedia live streaming in a distributed environment. Also, it has extended RMI which is a distributed object technology and JMF using multimedia transmission/processing. A java-based DLS package has been designed to separate a transmission and a control for more efficient distributed processing. It is possible to apply in development of multimedia service supported 1:N transmission and runned independently to any platform.

• The Journal of the Korea Contents Association
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• v.9 no.2
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• pp.51-59
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• 2009

Interactive multimedia broadcasting can serve various additional information of object in multimedia because of the commercialized data broadcasting by communication and broadcasting convergence. One of the most important factors in interactive multimedia broadcasting is User-Centric Interoperability. The higher User-Centric Interoperability, the more information of user-interest objects are served quickly by user request. This proposed method finds own area of the object in mask video and divides the area into equal parts. And then it store as a form of bitsum after clustering the area. As a result of experiment, We confirm the method is efficient to use space for storing position information of the object.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.139-147
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• 2014

In this paper, we present a novel method for simultaneous detection and tracking of multiple objects using dual-layer particle filtering. The proposed dual-layer particle sampling (DLPS) algorithm consists of parent-particles (PP) in the first layer for detecting multiple objects and child-particles (CP) in the second layer for tracking objects. In the first layer, PPs detect persons using a classifier trained by the intersection kernel support vector machine (IKSVM) at each particle under a randomly selected scale. If a certain PP detects a person, it generates CPs, and makes an object model in the detected object region for tracking the detected object. While PPs that have detected objects generate CPs for tracking, the rest of PPs still move for detecting objects. Experimental results show that the proposed method can automatically detect and track multiple objects, and efficiently reduce the processing time using the sampled particles based on motion distribution in video sequences.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.3
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• pp.55-63
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• 2008

This paper presents a panorama background generation and object tracking technique using a Pan-Tilt-Zoom camera. The proposed method estimates local motion vectors rapidly using phase correlation matching at the prespecified multiple local regions, and it makes minimized estimation error by vector quantization. We obtain the required image patches, by estimating the overlapped region using local motion vectors, we can then project the images to cylinder and realign the images to make the panoramic image. The object tracking is performed by extracting object's motion and by separating foreground from input image using background subtraction. The proposed PTZ-based object tracking method can efficiently generated a stable panorama background, which covers up to 360 degree FOV The proposed algorithm is designed for real-time implementation and it can be applied to many commercial applications such as object shape detection and face recognition in various surveillance video systems.

• The Transactions of the Korea Information Processing Society
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• v.7 no.4
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• pp.1062-1072
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• 2000

The applications developing in distributed object computing enviroments are faced with the difficulties for managing various lots of distributed objects. Also, because the most multimedia service, like video, audio, and so forth, must be satisfied itself with real-time constraints, the users also are feeling with necessary to apply real-time mechanisms to distributed multimedia services. The goal of this paper is to solve the problems for managing distributed objects, and to be easy to develop complex applications that can provide real-time services. To do this, we designed and implemented a real-time object group platform that can be placed between applications and CORBA. This platform is extended the existing object group model[13,14] added to the scheduler and timer object components for supporting real-time concept. We designed the components for platform by using James Rumbaugh object modeling technology that consists of object, function, and dynamic model. And then we described the detailed interfaces of the components by IDL, and implemented our real-time object group's platform using OrbixMT 22 which is the IONA Technologies' ORB product. Finally, we showed the execution procedures of the schduler object of each components in a real-time object group platform.

• Proceedings of the Korea Multimedia Society Conference
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• 1998.10a
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• pp.31.2-46
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• 1998

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.937-938
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• 2008

Spotlight system has been made use of art works on stage such as musical and performance etc. Currently, spotlight is controlled manually through the planned path in advance. Therefore, automatic control system is necessary for manipulating spotlight on stage. In this paper, we propose the system that detects to track the multiple objects and classifies those objects, also selects an object of those ones. The proposed method can be applied to the interactive stage spotlighting system(ISSS).

• Journal of Korea Multimedia Society
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• v.9 no.12
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• pp.1560-1571
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• 2006

In order to transmit multimedia streams over the network with a timely changing channel bandwidth such as Internet, scalable video coding schemes have been studied to represent video in flexible bitstream. Much research has been made on how to represent encoded media(such as video) bitstream in scalable ways. In this paper, rte propose an optimal selection of the objects for MPEG-4 bitstream adaptation to meet a given constraint. We adopt a multiple choice knapsack problem with multi-step selection for the MPEG-4 objects with different bit-rate scaling levels in the MPEG-4 bitstream. The bitstream adaptation based on the optimal selection result is then to fetch the necessary parts of the MPEG-4 bitstream to constitute an adapted version of the original MPEG-4 binary resource. The experiment results show that the optimal selection of MPEG-4 objects for a given constraint can promisingly be made which meets the given constraint.