• Proceedings of the Korean Information Science Society Conference
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• 2005.11a
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• pp.271-273
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• 2005

In wireless UDP data transfers, the handoff is one of the most breaking down things. To polycast multimedia data to several clients a sewer may connect clients by UDP networks. Mostly, video data must be compressed based on difference between before and next packets. Thus, the packet losses on the video stream may cause the recomposing of video data to be corrupt. This proposal provides simply retransmitting of lost packets according to a sequence and buffering packets in a given order.

• Journal of the Korea Computer Industry Society
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• v.7 no.5
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• pp.513-520
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• 2006

In this paper, we propose a novel real-time frame-layer rate control algorithm using sliding window method for low bit rate video coding. The proposed rate control method performs bit allocation at the frame level to minimize the average distortion over an entire sequence as well as variations in distortion between frames. A new frame-layer rate-distortion model is derived, and a non-iterative optimization method is used for low computational complexity. In order to reduce the quality fluctuation, we use a sliding window scheme which does not require the pre-analysis process. Therefore, the proposed algorithm does not produce time delay from encoding, and is suitable for real-time low-complexity video encoder. Experimental results indicate that the proposed control method provides better visual and PSNR performance than the existing TMN8 rate control method.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.281-286
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• 2007

비디오 복원(video completion)은 비디오 영상에서 색상값에 대한 정보가 없는 픽셀에 적절한 색을 채워 영상을 복원하는 기술이다. 본 논문에서는 움직이는 두 물체가 교차하는 입력영상으로부터 하나의 물체를 제거함으로 발생하는 홀(hole)을 채우는 비디오 복원 기술을 제안한다. 입력 영상에서의 두 물체 중 카메라와 가까운 물체를 제거함으로써 영상의 홀이 발생하게 되고, 이 홀을 다른 프레임들의 정보를 이용하여 채움으로써 가려진 물체를 복원한다. 모든 프레임에 대해 각 물체의 중심을 추정하여 물체의 중심을 기준으로 시-공간 볼륨(spatio-temporal volume)을 생성하고, 복셀 매칭(voxel matching)을 통한 시간적 탐색을 수행한 후 두 물체를 분리한다. 가리는 물체 영역으로 판단 된 부분을 삭제하고 공간적 탐색 방법을 이용하여 홀을 채워 가려짐이 있는 물체를 복원하는 과정을 소개한다. 실험 결과를 통해 제안한 기술이 비교적 자연스러운 결과를 얻을 수 있다는 것을 보여준다.

• Journal of information and communication convergence engineering
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• v.13 no.3
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• pp.197-204
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• 2015

In this paper, we present an algorithm for the detection of illegally parked vehicles based on a combination of some image processing algorithms. A digital camera is fixed in the illegal parking region to capture the video frames. An adaptive Gaussian mixture model (GMM) is used for background subtraction in a complex environment to identify the regions of moving objects in our test video. Stationary objects are detected by using the pixel-level features in time sequences. A stationary vehicle is detected by using the local features of the object, and thus, information about illegally parked vehicles is successfully obtained. An automatic alarm system can be utilized according to the different regulations of different illegal parking regions. The results of this study obtained using a test video sequence of a real-time traffic scene show that the proposed method is effective.

• 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.

• Journal of the Institute of Convergence Signal Processing
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• v.14 no.4
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• pp.231-234
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• 2013

This paper introduces a mixture of background subtraction technique and K-Means clustering algorithm for removing shadows from video sequences. Lighting conditions cause an issue with segmentation. The proposed method can successfully eradicate artifacts associated with lighting changes such as highlight and reflection, and cast shadows of moving object from segmentation. In this paper, K-Means clustering algorithm is applied to the foreground, which is initially fragmented by background subtraction technique. The estimated shadow region is then superimposed on the background to eliminate the effects that cause redundancy in object detection. Simulation results depict that the proposed approach is capable of removing shadows and reflections from moving objects with an accuracy of more than 95% in every cases considered.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2001.05a
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• pp.318-324
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• 2001

In this paper we propose the adaptive scheme to place more search points as long as the operation tapability of the motion estimator in the video codec permits. And the proposed algorithm takes advantage of the intuitive fact that the quality of the decoded video is more degraded as the spatial frequency of the corresponding block is increased due to the augmentation of local minima per unit area. Thererore, we propose the scheme to enhance the quality by locating relatively more search points in the block with high frequency components by analyzing the spatial frequencies of the video sequence. As a result, the proposed scheme can adaptively place more search points possibly permitted by the motion estimator and guarantees better quality compared to the TSS and FS.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04b
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• pp.691-693
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• 2002

현대 사회에서 수요자를 고려하지 않은 산업 형태는 거의 찾아볼 수 없다. 우리 교육 또한 학생 개개인의 능력을 출발점으로 하여 학생의 눈높이에 맞춘 교육을 바람직하게 여기는 추세로 변화하고 있다. 이렇게 볼 때 가장 이상적인 학습형태는 개별화 수업이다. 최근 데이터 압축 기술과 통신 기술의 발달로 동영상 데이터(video data)를 이용한 다양한 서비스가 가능하게 되면서 교육에서도 그 사용의 폭이 넓어지고 있다. 이에 따라 동영상 데이터를 효율적으로 저장, 관리할 수 있는 검색에 대한 연구가 활발하게 이루어져오고 있다. 본 논문에서는 동영상 데이터 검색방법의 하나인 주석기반 방식(text-based retrieval)을 이용하여 하나의 교육용 비디오를 장면분할(scene segmentation)하여 학습내용의 수준에 따라 상.중.하 색인을 한다. 이 색인된 비디오에서 수준별 개별학습이 가능한 가상의 비디오 시퀸스(video sequence)를 만들어낸다.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.372-374
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• 2003

The optical flow theory can be utilized for automatically tracking and positioning homologous points in digital video (DV) image sequences. In this paper, the Lucas-Kanade optical flow estimation (LKOFE) method and the normalized cross-correlation (NCC) method are compared and analyzed using the DV image sequences acquired by our SONY DCRPC115 DV camera. Thus, an improved optical flow estimation procedure, called 'Iterated Optical Flow Estimation (IOFE)', is presented. Our test results show that the trackable range of 3${\sim}$4 pixels in the LKOFE procedure can be apparently enlarged to 30 pixels in the IOFE.

• Journal of Broadcast Engineering
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• v.19 no.2
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• pp.257-267
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• 2014

Distributed compressive video sensing (DCVS) is a low cost sampling paradigm for video coding based on the compressive sensing and the distributed video coding. In this paper, we propose using a skip-mode coding in DCVS under the assumption that in case of high temporal correlation, temporal interpolation can guarantee sufficiently good quality of nonkey frame, therefore no need to transmit measurement data in such a nonkey frame. Furthermore, we extend it to use a hierarchical structure for better temporal interpolation. Simulation results show that the proposed skip-mode coding can save the average subrate of whole video sequence while the PSNR is reduced only slightly. In addition, by using the proposed scheme, the computational complexity is also highly decreased at decoder on average by 43.75% for video sequences that have strong temporal correlation.