• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.2C
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• pp.147-161
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• 2003

Video object segmentation is one of the core technologies for content-based real-time MPEG-4 encoding system. For real-time requirement, the segmentation algorithm should be fast and accurate but almost all existing algorithms are computationally intensive and not suitable for real-time applications. The MPEG-4 VM(Verification Model) has provided basic algorithms for MPEG-4 encoding but it has many limitations in practical software development, real-time camera input system and compression efficiency. In this paper, we implemented the preprocessing system for real-time camera input and VOP extraction for content-based video coding and also implemented motion detection to achieve the 180 : 1 compression rate for real-time and high compression MPEG-4 encoding.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.1
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• pp.77-85
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• 2018

This paper proposes a robust digital video stabilization algorithm to extract and track an object, which uses a phase correlation-based motion correction. The proposed video stabilization algorithm consists of background stabilization based on motion estimation and extraction of a moving object. The motion vectors can be estimated by calculating the phase correlation of a series of frames in the eight sub-images, which are located in the corner of the video. The global motion vector can be estimated and the image can be compensated by using the multiple local motions of sub-images. Through the calculations of the phase correlation, the motion of the background can be subtracted from the former frame and the compensated frame, which share the same background. The moving objects in the video can also be extracted. In this paper, calculating the phase correlation to track the robust motion vectors results in the compensation of vibrations, such as movement, rotation, expansion and the downsize of videos from all directions of the sub-images. Experimental results show that the proposed digital image stabilization algorithm can provide continuously stabilized videos and tracking object movements.

• ETRI Journal
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• v.44 no.1
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• pp.38-50
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• 2022

This paper presents a study on the use of encoder-derived features in decoder-side depth estimation. The scheme of multiview video encoding does not require the transmission of depth maps (which carry the geometry of a three-dimensional scene) as only a set of input views and their parameters are compressed and packed into the bitstream, with a set of features that could make it easier to estimate geometry in the decoder. The paper proposes novel recursive block splitting for the feature extraction process and evaluates different scenarios of feature-driven decoder-side depth estimation, performed by assessing their influence on the bitrate of metadata, quality of the reconstructed video, and time of depth estimation. As efficient encoding of multiview sequences became one of the main scopes of the video encoding community, the experimental results are based on the "geometry absent" profile from the incoming MPEG Immersive video standard. The results show that the quality of synthesized views using the proposed recursive block splitting outperforms that of the state-of-the-art approach.

• Journal of KIISE:Software and Applications
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• v.33 no.10
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• pp.851-861
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• 2006

The paper proposes a novel unsupervised video object segmentation algorithm for image sequences with low depth-of-field (DOF), which is a popular photographic technique enabling to represent the intention of photographer by giving a clear focus only on an object-of-interest (OOI). The proposed algorithm largely consists of two modules. The first module automatically extracts OOIs from the first frame by separating sharply focused OOIs from other out-of-focused foreground or background objects. The second module tracks OOIs for the rest of the video sequence, aimed at running the system in real-time, or at least, semi-real-time. The experimental results indicate that the proposed algorithm provides an effective tool, which can be a basis of applications, such as video analysis for virtual reality, immersive video system, photo-realistic video scene generation and video indexing systems.

• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.743-754
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• 2019

System for three degrees of freedom plus (3DoF+) and 6DoF requires multi-view high resolution 360 video transmission to provide user viewport adaptive 360 video streaming. In this paper, we implement 3DoF+ 360 video compression system which removes the redundancy between multi-view videos and merges the residual into one video to provide high quality 360 video corresponding to an user's head movement efficiently. Implementations about 3D warping based redundancy removal method between 3DoF+ 360 videos and residual extraction and merger are explained in this paper. With the proposed system, 20.14% of BD-rate reduction in maximum is shown compared to traditional high-efficiency video coding (HEVC) based system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.1
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• pp.123-127
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• 2005

This paper addresses the problem of extracting video objects from compressed video signals. Compressed videos include several informations about moving objects. An useful cue for object segmentation is motion vector per macroblock which sparse in MPEG. We propose a method for automatically estimating and extracting moving objects using motion vectors of macroblocks in this work.

• The Journal of the Acoustical Society of Korea
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• v.23 no.3E
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• pp.91-97
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• 2004

In this paper, we propose a classification system of TV program scenes based on audio information. The system classifies the video scene into six categories of commercials, basketball games, football games, news reports, weather forecasts and music videos. Two type of audio feature set are extracted from each audio frame-timbral features and coefficient domain features which result in 58-dimensional feature vector. In order to reduce the computational complexity of the system, 58-dimensional feature set is further optimized to yield l0-dimensional features through Sequential Forward Selection (SFS) method. This down-sized feature set is finally used to train and classify the given TV program scenes using κ -NN, Gaussian pattern matching algorithm. The classification result of 91.6% reported here shows the promising performance of the video scene classification based on the audio information. Finally, the system stability problem corresponding to different query length is investigated.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.229-232
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• 2009

Shot change detection is an important technique for effective management of video data, so detection scheme requires adaptive detection techniques to be used actually in various video. In this paper, we propose an adaptive shot change detection algorithm using the mean of feature value on variable reference blocks. Our algorithm determines shot change detection by defining adaptive threshold values with the feature value extracted from video frames and comparing the feature value and the threshold value. We obtained better detection ratio than the conventional methods maximally by 15% in the experiment with the same test sequence. We also had good detection ratio for other several methods of feature extraction and could see real-time operation of shot change detection in the hardware platform with low performance was possible by implementing it in TVUS model of HOMECAST Company. Thus, our algorithm in the paper can be useful in PMP or other portable players.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.11a
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• pp.169-171
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• 2011

최근 통신 환경의 진화와 고사양 모바일 단말기의 대중화로 인하여 모바일 통신 환경에서 동영상 서비스를 이용하는 사용자가 급증하고 있다. 사용자들은 제한적인 데이터 사용량을 이용하여 필요한 영상을 효율적으로 검색 및 탐색하기 위하여 미리보기 서비스 또는 Thumbnail을 이용한다. 이 중 Thumbnail은 동영상의 복호화 과정에서 제공되는 서비스이며, 이를 효과적으로 추출하는데 있어서 낮은 복잡도의 기술들이 사용되어야 한다. 본 논문에서는 영상의 히스토그램의 특징을 이용한 Thumbnail 추출 기법을 제안한다. 제안하는 추출 기법에서는 각 영상의 히스토그램을 비교 및 분석하여 하나의 video을 다수의 구간으로 분할하고, 각 구간의 대표 Thumbnail을 추출하는 방법을 사용한다. 다양한 영상을 이용한 실험 결과는 제안하는 알고리즘이 효과적으로 Thumbnail을 추출함을 보여준다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5506-5521
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• 2017

Three-dimensional video (3DV), as the new generation of video format standard, can provide the viewers with a vivid screen sense and a realistic stereo impression. Meanwhile the view synthesis has become an important issue for 3DV application. Differently from the conventional methods based on depth, in this paper we propose a new view synthesis algorithm, which can employ the correlation among views and warp in the image domain only. There are mainly two contributions. One is the incorporation of sobel edge points into feature extraction and matching, which can obtain a better stable homography and then a visual comfortable synthesis view compared to SIFT points only. The other is a novel image blending method proposed to obtain a better synthesis image. Experimental results demonstrate that the proposed method can improve the synthesis quality both in subjectivity and objectivity.