• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.17-19
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• 2007

This paper describe an interactive video object segmentation tool which can be used to generate MPEG-4 video object planes for multimedia broadcasting and enables content based functionalities. In order to apply these functionalities, each frame of video sequence should be represented in terms of video objects. Semiautomatic segmentation can be thought of as a user-assisted segmentation technique. A user can initially mark objects of interest around the real object boundaries. Then the user-guided and selected objects are continuously separated from the unselected areas though time evolution in the image sequences. We proposed method shows very promising result and this encourages the development of object based video editing system.

• The Transactions of the Korea Information Processing Society
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• v.7 no.5
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• pp.1570-1578
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• 2000

Object motion is an important feature of content in video sequences. By now, various methods to exact feature about the object motion have been reported[1,2]. However they are not suitable to index video using the motion, since a lot of bits and complex indexing parameters are needed for the indexing [3,4] In this paper, we propose object motion map which could provide efficient indexing method for object motion. The proposed object motion map has both global and local motion information during an object is moving. Furthermore, it requires small bit of memory for the indexing. to evaluate performance of proposed indexing technique, experiments are performed with video database consisting of MPEG-1 video sequence in MPEG-7 test set.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.07a
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• pp.42-45
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• 2010

This paper proposes an intelligent video surveillance system for human object tracking. The proposed system integrates the object extraction, human object recognition, face detection, and camera control. First, the object in the video signals is extracted using the background subtraction. Then, the object region is examined whether it is human or not. For this recognition, the region-based shape descriptor, angular radial transform (ART) in MPEG-7, is used to learn and train the shapes of human bodies. When it is decided that the object is human or something to be investigated, the face region is detected. Finally, the face or object region is tracked in the video, and the pan/tilt/zoom (PTZ) controllable camera tracks the moving object with the motion information of the object. This paper performs the simulation with the real CCTV cameras and their communication protocol. According to the experiments, the proposed system is able to track the moving object(human) automatically not only in the image domain but also in the real 3-D space. The proposed system reduces the human supervisors and improves the surveillance efficiency with the computer vision techniques.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.929-946
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• 2022

Free viewpoint video (FVV) service is an immersive media service that allows a user to watch it from a desired location or viewpoint. It is composed of various forms according to the direction of the viewpoint of the provided video, and includes zoom in/out in the service. As consumers' demand for active watching is increasing, the importance of FVV services is expected to grow gradually. However, additional considerations are needed to seamlessly stream FVV service. FVV includes a plurality of videos, video changes may occur frequently due to movement of the viewpoint. Frequent occurrence of video switching or re-request another video can cause service delay and it also can lower user's quality of service (QoS). In this case, we assumed that if a video showing an object that the user wants to watch is selected and provided, it is highly likely to meet the needs of the viewer. In particular, it is important to provide an object-oriented FVV service when zooming in. When video zooming in in the usual way, it cannot be guaranteed to zoom in around the object. Zoom function does not consider about video viewing. It only considers the viewing screen size and it crop the video view as fixed screen location. To solve this problem, we propose a zoom in/out method of object-centered dynamic adaptive streaming of FVV in this paper. Through the method proposed in this paper, users can enjoy the optimal video service because they are provided with the desired object-based video.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1434-1449
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• 2019

Video object segmentation is a significant task in computer vision, but its performance is not very satisfactory. A method of video object segmentation using weakly temporal information is presented in this paper. Motivated by the phenomenon in reality that the motion of the object is a continuous and smooth process and the appearance of the object does not change much between adjacent frames in the video sequences, we use a feed-forward architecture with motion estimation to predict the mask of the current frame. We extend an additional mask channel for the previous frame segmentation result. The mask of the previous frame is treated as the input of the expanded channel after processing, and then we extract the temporal feature of the object and fuse it with other feature maps to generate the final mask. In addition, we introduce multi-mask guidance to improve the stability of the model. Moreover, we enhance segmentation performance by further training with the masks already obtained. Experiments show that our method achieves competitive results on DAVIS-2016 on single object segmentation compared to some state-of-the-art algorithms.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.4
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• pp.115-121
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• 2016

Recently, it has become an important problem to extract semantic objects from videos, which are useful for improving the performance of video compression and video retrieval. In this thesis, an automatic extraction method of moving objects of interest in video is suggested. We define that an moving object of interest should be relatively large in a frame image and should occur frequently in a scene. The moving object of interest should have different motion from camera motion. Moving object of interest are determined through spatial continuity by the AMOS method and moving histogram. Through experiments with diverse scenes, we found that the proposed method extracted almost all of the objects of interest selected by the user but its precision was 69% because of over-extraction.

• Journal of the Korea Society for Simulation
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• v.12 no.2
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• pp.25-34
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• 2003

Because of explosive growth in demand for web-based multimedia applications, proper proxy caching for large multimedia object (especially video) has become needed. For a video object which is much larger in size and has different access characteristics than the traditional web object such as image and text, caching the whole video file as a single web object is not efficient for the proxy cache. In this paper, we propose a proxy caching strategy with the constant-sized segment for video file and an improved proxy cache replacement policy. Through the event-driven simulation under various conditions, we show that our proposal is more efficient than the variable-sized segment strategy which has been proven to have higher hit ratio than other traditional proxy cache strategies.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.11A
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• pp.1098-1103
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• 2005

The edge and contour information are very much appreciated by the human visual systems and are responsible for our perceptions and recognitions. Therefore, if edge information is integrated during extracting video objects, we can generate boundaries of oects closer to human visual systems for multimedia applications such as interaction between video objects, object-based coding, and representation. Most of object extraction methods are difficult to implement real-time systems due to their iterative and complex arithmetic operations. In this paper, we propose a VLSI architecture integrating edge information to extract video objects for precisely located object boundaries. The proposed architecture can be easily implemented into hardware due to simple arithmetic operations. Also, it can be applied to real-time object extraction for object-oriented multimedia applications.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.202-205
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• 2000

In this paper we propose an algorithm that detects, tracks a moving object, and classify whether it is human from the video clip captured under the fixed video camera. It detects the outline of the moving object by finding out the local maximum points of the modulus image, which is the magnitude of the motion vectors. It also estimates the size and the center of the moving object. When the object is detected, the algorithm discriminates whether it is human by segmenting the face. It is segmented by searching the elliptic shape using Hough transform and grouping the skin color region within the elliptic shape.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.294-297
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• 2009

Multi-view video consists of a set of multiple video sequences from multiple viewpoints or view directions in the same scene. It contains extremely a large amount of data and some extra information to be stored or transmitted to the user. This paper presents inter-view correlations among video objects and the background to reduce the prediction complexity while achieving a high coding efficiency in multi-view video coding. Our proposed algorism is based on object-based segmentation scheme that utilizes video object information obtained from the coded base view. This set of data help us to predict disparity vectors and motion vectors in enhancement views by employing object registration, which leads to high compression and low-complexity coding scheme for enhancement views. An experimental results show that the superiority can provide an improvement of PSNR gain 2.5.3 dB compared to the simulcast.