• Proceedings of the Korean Information Science Society Conference
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• 2002.04b
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• pp.109-111
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• 2002

Visual organs play an important role in human information recognition processes. If they are expressed in a way of digital information, it makes much bigger amount of visual information among any other information. For that reason, MPEG-2 has been taken use of to represent information compressing technology in multi-media. Although the imported data would basically contain noises, when original video images are encoded into MPET-2. Accordingly, we propose soft- $\alpha$ filter to improve image quality of digital image received from the actual image and to reduce noises from them. We also propose a method combining vertical/horizontal filter and soft- $\alpha$ filter on MPEG-2 video image. We can get two kinds of effects from the advantages of this kind of combination. Firstly, it will reduce processing time ducting horizontal and vetical filtering process. It will cover time for soft- $\alpha$ filter. Secondly, it will simplify the colors in horizontal and vertical filter. Therefore we can get clearer quality without noises from soft- $\alpha$ filter.

• JSTS:Journal of Semiconductor Technology and Science
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• v.7 no.4
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• pp.229-234
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• 2007

In this paper, we present an efficient instruction set architecture using vector register file hardware to accelerate operation of general matrix-vector operations in DSP microprocessor. The technique enables in-situ row-access as well as column access to the register files. It can reduce the number of memory access significantly. The technique is especially useful for block-based video signal processing kernels such as FFT/IFFT, DCT/IDCT, and two-dimensional filtering. We have applied the new instruction set architecture to in-loop deblocking filter processing in H.264 decoder. Performance comparisons show that the required load/store operations for the in-loop deblocking filter can be reduced about 42%. The architecture would improve the processing speed, and code density in DSP microprocessor especially for video signal processing substantially.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1998.06b
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• pp.29-33
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• 1998

In this paper, we propose a hierarchical segmentation method for tracking a semantic video object using a watershed algorithm based on morphological filtering. In the proposed method, each hierarchy consists of three steps: First, markers are extracted on the simplified current frame. Second, region growing by a modified watershed algorithm is performed for segmentation. Finally, the segmented regions are classified into 3 categories, i.e., inside, outside, and uncertain regions according to region probability values, which are acquired by the probability map calculated from a estimated motion field. Then, for the remaining uncertain regions, the above three steps are repeated at lower hierarchies with less simplified frames until every region is decided to a certain region. The proposed algorithm provides prospective results in video sequences such as Miss America, Clair, and Akiyo.

• MALSORI
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• no.63
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• pp.139-151
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• 2007

As the Internet becomes prevalent in our lives, harmful contents, such as phornographic videos, have been increasing on the Internet, which has become a very serious problem. To prevent such an event, there are many filtering systems mainly based on the keyword-or image-based methods. The main purpose of this paper is to devise a system that classifies pornographic videos based on the audio information. We use the mel-cepstrum modulation energy (MCME) which is a modulation energy calculated on the time trajectory of the mel-frequency cepstral coefficients (MFCC) as well as the MFCC as the feature vector. For the classifier, we use the well-known Gaussian mixture model (GMM). The experimental results showed that the proposed system effectively classified 98.3% of pornographic data and 99.8% of non-pornographic data. We expect the proposed method can be applied to the more accurate classification system which uses both video and audio information.

• ETRI Journal
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• v.37 no.3
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• pp.551-561
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• 2015

We propose a novel multiple-object tracking algorithm for real-time intelligent video surveillance. We adopt particle filtering as our tracking framework. Background modeling and subtraction are used to generate a region of interest. A two-step pedestrian detection is employed to reduce the computation time of the algorithm, and an iterative particle repropagation method is proposed to enhance its tracking accuracy. A matching score for greedy data association is proposed to assign the detection results of the two-step pedestrian detector to trackers. Various experimental results demonstrate that the proposed algorithm tracks multiple objects accurately and precisely in real time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.9
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• pp.3177-3195
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• 2014

In many moving object detection problems of an aerial video, accurate and robust stabilization is of critical importance. In this paper, a novel accurate image alignment algorithm for aerial electronic image stabilization (EIS) is described. The feature points are first selected using optimal derivative filters based Harris detector, which can improve differentiation accuracy and obtain the precise coordinates of feature points. Then we choose the Delaunay Triangulation edges to find the matching pairs between feature points in overlapping images. The most "useful" matching points that belong to the background are used to find the global transformation parameters using the projective invariant. Finally, intentional motion of the camera is accumulated for correction by Sage-Husa adaptive filtering. Experiment results illustrate that the proposed algorithm is applied to the aerial captured video sequences with various dynamic scenes for performance demonstrations.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.134-137
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• 2009

최근 마이크로소프트 (Microsoft)에서 발표된 후 주목 받고 있는 JPEG XR 은 압축 효율 면에서 뛰어난 장점을 가지고 있다. 일반적으로 JPEG XR 은 기존의 JPEG 과는 다른 압축 과정과 주파수 성분 분포를 가지고 있다고 알려져 있다. 하지만 JPEG 압축 방식과 비교하여 JPEG XR 의 압축영역에서의 영상 필터 처리의 연구는 아직 미흡한 실정이다. 본 논문에서는 JPEG XR 의 압축과정과 주파수 성분 분포의 분석을 기반으로 효율적인 저역/고역통과 필터 함수를 제안하고, 체계적인 실험을 통해 제안한 필터함수의 효율성을 입증하였다.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.31-38
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• 2023

This paper introduces a real-time face swapping system that enables video influencers to swap their faces with arbitrary generated face images of their choice. The system is implemented as a Django-based server that uses a REST request to communicate with the generative model,specifically the pretrained stable diffusion model. Once generated, the generated image is displayed on the front page so that the influencer can decide whether to use the generated face or not, by clicking on the accept button on the front page. If they choose to use it, both their face and the generated face are sent to the landmark extraction module to extract the landmarks, which are then used to swap the faces. To minimize the fluctuation of landmarks over time that can cause instability or jitter in the output, a temporal filtering step is added. Furthermore, to increase the processing speed the system works on a reduced set of the extracted landmarks.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.239-241
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• 2022

MIV(MPEG Immersive Video) 표준은 제한된 3D 공간의 다양한 위치의 뷰(view)들을 효율적으로 압축하여 사용자에게 임의의 위치 및 방향에 대한 6 자유도(6DoF)의 몰입감을 제공한다. MIV 의 참조 소프트웨어인 TMIV(Test Model for Immersive Video)에서는 몰입감을 제공하기 위한 여러 시점의 입력 뷰들 간의 중복 영역을 제거하고 남은 영역들을 패치(patch)로 만들어 패킹(packing)한 아틀라스(atlas)를 생성하고 이를 압축 전송한다. 아틀라스 영상은 일반적인 영상 달리 많은 불연속성을 포함하고 있으며 이는 부호화 효율을 크게 저하시키다 본 논문에서는 아틀라스 영상의 부호화 손실을 줄이기 위한 신경망 기반의 후처리 필터링 기법을 제시한다. 제안기법은 기존의 TMIV 와 비교하여 아틀라스의 복원 화질 향상을 보여준다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.12
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• pp.5856-5864
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• 2011

In this paper, we propose a moving object detection method in road video sequences acquired from a stationary camera. Our proposed method is based on the background subtraction method using Gaussian pyramids in both the background images and input video frames. It is more effective than pixel based subtraction approaches to reduce false detections which come from the mis-registration between current frames and the background image. And to determine a threshold value automatically in subtracted images, we calculate the threshold value using Otsu's method in each frame and then apply a scalar Kalman filtering to the threshold value. Experimental results show that the proposed method effectively detects moving objects in road video images.