• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.4
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• pp.1-8
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• 2010

This paper proposes a new frame rate up-conversion method. First, the proposed triple frame-based bidirectional motion estimation method reduce block artifacts in the interpolated frame by solving the wrong motion estimation in the area with similar characteristics. Second, the proposed motion vector smoothing reduces outliers, which result in block artifacts, considering the spatio-temporal neighboring motion vectors. In the experiments, the proposed frame rate up-conversion method improves the average PSNR and SSIM by up to 4.337 dB and 0.089, respectively, compared to the existing methods.

• Journal of KIISE:Software and Applications
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• v.29 no.4
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• pp.235-247
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• 2002

For an efficient indexing and retrieval of digital video data, research on video caption extraction and recognition is required. This paper proposes methods for extracting artificial captions from video data and enhancing their image quality for an accurate Hangul and English character recognition. In the proposed methods, we first find locations of beginning and ending frames of the same caption contents and combine those multiple frames in each group by logical operation to remove background noises. During this process an evaluation is performed for detecting the integrated results with different caption images. After the multiple video frames are integrated, four different image enhancement techniques are applied to the image: resolution enhancement, contrast enhancement, stroke-based binarization, and morphological smoothing operations. By applying these operations to the video frames we can even improve the image quality of phonemes with complex strokes. Finding the beginning and ending locations of the frames with the same caption contents can be effectively used for the digital video indexing and browsing. We have tested the proposed methods with the video caption images containing both Hangul and English characters from cinema, and obtained the improved results of the character recognition.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.4
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• pp.95-102
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• 2004

In order to process video data effectively, it is required that the content information of video data is loaded in database and semantic-based retrieval method can be available for various query of users. Currently existent contents-based video retrieval systems search by single method such as annotation-based or feature-based retrieval, and show low search efficiency md requires many efforts of system administrator or annotator because of imperfect automatic processing. In this paper, we propose semantics-based video retrieval system which support semantic retrieval of various users by feature-based retrieval and annotation-based retrieval of massive video data. By user's fundamental query and selection of image for key frame that extracted from query, the agent gives the detail shape for annotation of extracted key frame. Also, key frame selected by user become query image and searches the most similar key frame through feature based retrieval method and optimized comparison area extracting that propose. Therefore, we propose the system that can heighten retrieval efficiency of video data through semantics-based retrieval.

• Journal of the Korea Computer Industry Society
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• v.5 no.2
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• pp.203-216
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• 2004

In order to process video data effectively, it is required that the content information of video data is loaded in database and semantic- based retrieval method can be available for various query of users. Currently existent contents-based video retrieval systems search by single method such as annotation-based or feature-based retrieval, and show low search efficiency and requires many efforts of system administrator or annotator form less perfect automatic processing. In this paper, we propose semantic-based video retrieval system which support semantic retrieval of various users by feature-based retrieval and annotation-based retrieval of massive video data. By user's fundamental query and selection of image for key frame that extracted from query, the agent gives the detail shape for annotation of extracted key frame. Also, key frame selected by user become query image and searches the most similar key frame through feature based retrieval method that propose. Therefore, we design the system that can heighten retrieval efficiency of video data through semantic-based retrieval.

• Journal of Korea Multimedia Society
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• v.9 no.1
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• pp.127-137
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• 2006

In order to process video data effectively, it is required that the content information of video data is loaded in database and semantic- based retrieval method can be available for various query of users. Currently existent contents-based video retrieval systems search by single method such as annotation-based or feature-based retrieval, and show low search efficiency and requires many efforts of system administrator or annotator form less perfect automatic processing. In this paper, we propose semantic-based video retrieval system which support semantic retrieval of various users by feature-based retrieval and annotation-based retrieval of massive video data. By user's fundamental query and selection of image for key frame that extracted from query, the automatic indexing agent gives the detail shape for annotation of extracted key frame. Also, key frame selected by user become query image and searches the most similar key frame through feature based retrieval method that propose. Therefore, we propose the system that can heighten retrieval efficiency of video data through semantic-based retrieval.

• The KIPS Transactions:PartB
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• v.10B no.6
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• pp.687-694
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• 2003

According to the rapid increase of multimedia data quantity recently, various means of video data search has been desired. In order to process video data effectively, it is required that the content information of video data is loaded in database and semantic-based retrieval method can be available for various query of users. Currently existent contents-based video retrieval systems search by single method such as annotation-based or feature-based retrieval, and show low search efficiency and requires many efforts of system administrator or annotator form less perfect automatic processing. In this paper, we propose semantic-based video retrieval system which support semantic retrieval of various users by feature-based retrieval and annotation-based retrieval of massive video data. By user's fundamental query and selection of image for key frame that extracted from query, the agent gives the detail shape for annotation of extracted key frame. Also, key frame selected by user become query image and searches the most similar key frame through feature based retrieval method that propose. Therefore, we design the system that can heighten retrieval efficiency of video data through semantic-based retrieval.

• Annual Conference on Human and Language Technology
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• 2023.10a
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• pp.253-257
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• 2023

최근 다양한 대화 시스템이 스마트폰 어시스턴트, 자동 차 내비게이션, 음성 제어 스피커, 인간 중심 로봇 등의 실세계 인간-기계 인터페이스에 적용되고 있다. 하지만 대부분의 대화 시스템은 텍스트 기반으로 작동해 다중 모달리티 입력을 처리할 수 없다. 이 문제를 해결하기 위해서는 비디오와 같은 다중 모달리티 장면 인식을 통합한 대화 시스템이 필요하다. 기존의 비디오 기반 대화 시스템은 주로 시각, 이미지, 오디오 등의 다양한 자질을 합성하거나 사전 학습을 통해 이미지와 텍스트를 잘 정렬하는 데에만 집중하여 중요한 행동 단서와 소리 단서를 놓치고 있다는 한계가 존재한다. 본 논문은 이미지-텍스트 정렬의 사전학습 임베딩과 행동 단서, 소리 단서를 활용해 비디오 기반 대화 시스템을 개선한다. 제안한 모델은 텍스트와 이미지, 그리고 오디오 임베딩을 인코딩하고, 이를 바탕으로 관련 프레임과 행동 단서를 추출하여 발화를 생성하는 과정을 거친다. AVSD 데이터셋에서의 실험 결과, 제안한 모델이 기존의 모델보다 높은 성능을 보였으며, 대표적인 이미지-텍스트 자질들을 비디오 기반 대화시스템에서 비교 분석하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.277-279
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• 2013

스크램블링(Scrambling)은 네트워크에서 영상을 전송할 때 보안을 위해 데이터를 특정한 키에 의해 암호화 하여 전송함으로써, 수신자만이 원본 영상으로 복원할 수 있도록 하는 기술이다. 스크램블링은 전송에서 TDES, AES 뿐만아닌 SEED, AIRA의 암호화 알고리즘을 사용한다. 이 경우 암복호화에 많은 시간이 소요되어 실시간 전송환경에서는 전송속도 저하에 따른 QoS 문제가 발생한다. 이와 같은 문제를 해결하기 위해 기존 연구에서는 속도가 빠른 해쉬 함수를 이용하여 스크램블링 암호화 하는 기법을 제안하였다. 하지만 원본 이미지의 일부가 노출될 경우 이후 원본프레임이 노출될 수 있는 문제점을 가지고 있다. 본 논문에서는 이러한 문제점을 방지하기 위해 다중 해쉬 키 프레임을 이용한 Multi Hash key Frame based Scrambling Encryption 알고리즘을 제안한다. 성능평가에서는 제안하는 스크램블링 기법에 대한 암복호화 비용과 성능을 측정하였으며, 기존기법과 비교하였을 때 원본 노출로 인한 대입공격 취약성 부분을 기존 해쉬 함수의 보안 안전성만큼 향상시켰다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.10
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• pp.2417-2426
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• 2014

Remote gaze tracking system calculates the gaze from captured images that reflect infra-red LEDs in cornea. Glint is the point that reflect infra-red LEDs to cornea. Recently, remote gaze tracking system uses a number of IR-LEDs to make the system less prone to head movement and eliminate calibration procedure. However, in some cases, some of glints are unable to spot. In this case, it is impossible to calculate gaze. This study examines patterns of glints that are difficult to detect in remote gaze tracking system. Afterward, we propose an algorithm to reconstruct positions of missing glints that are difficult to detect using other detected glints. Based on this algorithm, we increased the number of valid image frames in gaze tracking experiments, and reduce errors of gaze tracking results by correcting glint's distortion in the reconstruction phase.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.374-375
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• 2022

Recently, Metaverse service has been widely used to naturally communicate with a remote location, freeing from time and spatial constraints. In order to produce such contents, it is necessary to restore and synthesize a 3D model based on real space data. In this paper, a 3D-generated reconstruction model is produced based on continuous images using multiple cameras and a technique to correct the reconstructed 3D model is presented. For this. offline multi-camera setup was performed, errors were analyzed on the 3D model created through images obtained from various angles, and correction was performed using a matching technique between image frames. It is expected that 3D reconstructed data can be utilized in various service fields such as culture, tourism, and medical care.