• Journal of the Korea Society of Computer and Information
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• v.12 no.5
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• pp.163-170
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• 2007

In this paper, We propose a new technique for extraction of moving objects included in compressed video signal. Moving object extraction is used in several fields such as contents based retrieval and target tracking. In this paper, in order to extract moving object blocks, motion vectors and DCT coefficients are used selectively. The proposed algorithm has a merit that it is no need of perfect decoding, because it uses only coefficients on the DCT transform domain. We used three test video sequences in the computer simulation, and obtained satisfactory results.

• Journal of Broadcast Engineering
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• v.3 no.1
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• pp.50-60
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• 1998

This paper addresses a problem of extraction of parameteric motion estimation and structural motion segmentation for compact image sequence representation and object-based generic video coding. In order to extract meaningful motion structure from image sequences, a direct parameteric motion estimation based on a pre-segmentation is proposed. The pre-segmentation which considers the motion of the moving objects is canied out based on probabilistic clustering with mixture models using optical flow and image intensities. Parametric motion segmentation can be obtained by iterated estimation of motion model parameters and region reassignment according to a criterion using Gauss-Newton iterative optimization algorithm. The efficiency of the proposed methoo is verified with computer simulation using elF real image sequences.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.269-272
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• 2001

In speech recognition technology, the utterance of every talker have special resonant frequency according to shape of talker's lip and to the motion of tongue. And utterances are different according to each talker. Accordingly, we need the superior moth-od of speech feature parameter extraction which reflect talker's characteristic well. This paper suggests the modified-MfCC combined existing MFCC with gammatone filter. We experimented with speech data from telephone and then we obtained results of enhanced speech recognition rate which is higher than that of the other methods.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.84.4-84
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• 2001

In this paper, we present a method to classify electromyogram (EMG) signals which are utilized to be control signals for patient-responsive walker-supported system for paraplegics. Patterns of EMG signals for dierent walking motions are classied via adequate filtering, real EMG signal extraction, AR-modeling, and modified self-organizing feature map (MSOFM). More efficient signal processing is done via a data-reducing extraction algorithm. Moreover, MSOFM classifies and determines the classified results are presented for validation.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.3
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• pp.91-102
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• 2004

In this paper, a fast information extraction algorithm for object-based MPEG-4 application from MPEG-1,2 is proposed. For object-based MPEG-4 conversion, we need to extract such information as object-image, shape-image, macro-block motion vector, and header information from MPEG-1,2 bit-stream. If we use the extracted information, fast conversion for object-based MPEG-4 is possible. The proposed object extraction algerian has two important steps, namely the motion vector extraction from MPEG-1,2 bit-stream and the watershed algerian The algorithm extracts objects using user's assistance in the intra frame and tracks then in the following inter frames. If we have an unsatisfactory result for a fast moving object the user can intervene to connect the segmentation. The proposed algorithm consist of two steps, which are intra frame object extracting processing and inter frame tracking processing. Object extracting process is the step in which user extracts a semantic object directly by using the block classification and watersheds. Object tracking process is the step of the following the object in the subsequent frames. It is based on the boundary fitting method using motion vector, object-mask and modified watersheds. Experimental results show that the proposed method can achieve a fast conversion from the MPEG-1,2 bit-stream to the object-based MPEG-4 input.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.333-336
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• 2001

본 논문에서는 영상 시퀀스 상에서 물체의 가려짐을 고려하여 상대적인 깊이 순서에 의해 정렬되는 계층을 분리하기 위한 새로운 움직임 분할 방법을 제안한다. 블록을 기반으로 한 움직임 추정 및 클러스터링 과정을 통하여 각 계층에 대한 블록영역을 구하고, 이 블록영역에 대하여 윤곽선 추출을 이용하여 각 계층에 대한 정확한 객체를 분리할 수 있다. 이러한 움직임 분할방법을 통한 동영상의 계층적인 표현은 영상에서 원하지 않는 물체, 전경, 배경의 제거나 기존의 영상을 이용한 새로운 영상의 합성에 이용될 수 있으며, 분할을 통해 얻어진 객체는 영상 압축, 영상 합성 등을 위한 데이터베이스에 저장되어 응용될 수 있다.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1999.05a
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• pp.154-162
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• 1999

This paper introduces the research and development of automatic generation technology to develop the character agent. The R&D of this technology includes three major elements-body model generation, automatic motion generation and synthetic human generation. Main areas of application would be cyber space- 3D game, animation, virtual shopping, on line chatting, virtual education system, simulation and security system.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1997.11a
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• pp.129-133
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• 1997

카메라로부터 얻은 영상은 이를 얻는 과정에서 카메라의 떨림 및 추가되는 노이즈에 의하여 손상을 입을 수 있으며, 이런 과정으로 손상된 영상에는 움직임 번짐현상(motion blur)이 발생하며 이는 영상의 명확도를 현저하게 떨어지게 한다. 움직임 번짐현상은 주파수 영역에서 움직임의 방향으로 주기적인 영점을 발생시키며 그 주기는 움직임의 길이에 반비례한다. 이러한 영점은 원 영상에 의한 영점과 노이즈에 의하여 소실되므로 이들의 영향을 power 영역에서의 평균법으로 최소화시킬 필요가 있다. 본 논문에서는 원영상과 노이즈의 영향인 최소화된 상태에서 2차원 cepstrum을 통하여 번짐현상을 주기와 방향을 계산해내는 알고리즘을 제안한다.

• Journal of Korea Multimedia Society
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• v.15 no.6
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• pp.731-736
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• 2012

Latest digital cinema is getting more interest on recent days. The combination of visually immersive 3D movie with chair movements and other physical effects has added more enjoyment. The movement of the chair is controlled manually in these digital cinemas. By the analysis of the digital cinema's video sequences, movement of the chair can be controlled automatically. In the proposed method first of all the motion of focused object and the background is identified and then the motion vector information is extracted by using the 9-search range. The motion vector is determined only for the movement of background while the object is stationary. The extracted Motion information from the digital cinemas is used for the movement control of the chair. The experimental results show that the proposed method outperforms the existing methods in terms of accuracy.

• 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.