• Title/Summary/Keyword: Directional Broadcast

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Adaptive Selection of Weighted Quantization Matrix for H.264 Intra Video Coding (H.264 인트라 부호화를 위한 적응적 가중치 양자화 행렬 선택방법)

  • Cho, Jae-Hyun;Cho, Suk-Hee;Jeong, Se-Yoon;Song, Byung-Cheol
    • Journal of Broadcast Engineering
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    • v.15 no.5
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    • pp.672-680
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    • 2010
  • This paper presents an adaptive quantization matrix selection scheme for H.264 video encoding. Conventional H.264 coding standard applies the same quantization matrix to the entire video sequence without considering local characteristics in each frame. In this paper, we propose block adaptive selection of quantization matrix according to edge directivity of each block. Firstly, edge directivity of each block is determined using intra prediction modes of its spatially adjacent blocks. If the block is decided as a directional block, new weighted quantization matrix is applied to the block. Otherwise, conventional quantization matrix is used for quantization of the non-directional block. Since the proposed weighted quantization is designed based on statistical distribution of transform coefficients in accordance with intra prediction modes, we can achieve high coding efficiency. Experimental results show that the proposed scheme can improve coding efficiency by about 2% in terms of BD bit-rate.

Video Highlight Prediction Using Multiple Time-Interval Information of Chat and Audio (채팅과 오디오의 다중 시구간 정보를 이용한 영상의 하이라이트 예측)

  • Kim, Eunyul;Lee, Gyemin
    • Journal of Broadcast Engineering
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    • v.24 no.4
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    • pp.553-563
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    • 2019
  • As the number of videos uploaded on live streaming platforms rapidly increases, the demand for providing highlight videos is increasing to promote viewer experiences. In this paper, we present novel methods for predicting highlights using chat logs and audio data in videos. The proposed models employ bi-directional LSTMs to understand the contextual flow of a video. We also propose to use the features over various time-intervals to understand the mid-to-long term flows. The proposed Our methods are demonstrated on e-Sports and baseball videos collected from personal broadcasting platforms such as Twitch and Kakao TV. The results show that the information from multiple time-intervals is useful in predicting video highlights.

Implementation of Omni-directional Image Viewer Program for Effective Monitoring (효과적인 감시를 위한 전방위 영상 기반 뷰어 프로그램 구현)

  • Jeon, So-Yeon;Kim, Cheong-Hwa;Park, Goo-Man
    • Journal of Broadcast Engineering
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    • v.23 no.6
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    • pp.939-946
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    • 2018
  • In this paper, we implement a viewer program that can monitor effectively using omni-directional images. The program consists of four modes: Normal mode, ROI(Region of Interest) mode, Tracking mode, and Auto-rotation mode, and the results for each mode is displayed simultaneously. In the normal mode, the wide angle image is rendered as a spherical image to enable pan, tilt, and zoom. In ROI mode, the area is displayed expanded by selecting an area. And, in Auto-rotation mode, it is possible to track the object by mapping the position of the object with the rotation angle of the spherical image to prevent the object from deviating from the spherical image in Tracking mode. Parallel programming for processing of multiple modes is performed to improve the processing speed. This has the advantage that various angles can be seen compared with surveillance system having a limited angle of view.

An Efficient Directional MAC Protocol for Vehicular Ad-hoc Networks (차량 Ad-hoc에서 효율적인 메시지 전달을 위한 지향성 MAC 프로토콜)

  • Ji, Soonbae;Kim, Junghyun;You, Cheolwoo
    • Journal of the Institute of Electronics and Information Engineers
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    • v.52 no.4
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    • pp.9-16
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    • 2015
  • Quick and safe message transmission is an important research topic of vehicular ad hoc networks (VANET). Most studies assume that the periodic broadcast of beacon-frames between vehicles increases the safety of the driver. In this paper, we propose a medium access control (MAC) protocol and location-based clustering for the VANET to support reliable data transfer. In our proposal, the cluster heade (CH) manage the access and allocate the resources of the node. Our proposal uses simulation to confirm the reduction of the transmission delay and the collision rate of the signal.

Face Recognition using High-order Local Pattern Descriptor and DCT-based Illuminant Compensation (DCT 기반의 조명 보정과 고차 지역 패턴 서술자를 이용한 얼굴 인식)

  • Choi, Sung-Woo;Kwon, Oh-Seol
    • Journal of Broadcast Engineering
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    • v.21 no.1
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    • pp.51-59
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    • 2016
  • This paper presents a method of DCT-based illuminant compensation to enhance the accuracy of face recognition under an illuminant change. The basis of the proposed method is that the illuminant is generally located in low-frequency components in the DCT domain. Therefore, the effect of the illuminant can be compensated by controlling the low-frequency components. Moreover, a directional high-order local pattern descriptor is used to detect robust features in the case of face motion. Experiments confirm the performance of the proposed algorithm got up to 95% when tested using a real database.

User Identification Method using Palm Creases and Veins based on Deep Learning (손금과 손바닥 정맥을 함께 이용한 심층 신경망 기반 사용자 인식)

  • Kim, Seulbeen;Kim, Wonjun
    • Journal of Broadcast Engineering
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    • v.23 no.3
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    • pp.395-402
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    • 2018
  • Human palms contain discriminative features for proving the identity of each person. In this paper, we present a novel method for user verification based on palmprints and palm veins. Specifically, the region of interest (ROI) is first determined to be forced to include the maximum amount of information with respect to underlying structures of a given palm image. The extracted ROI is subsequently enhanced by directional patterns and statistical characteristics of intensities. For multispectral palm images, each of convolutional neural networks (CNNs) is independently trained. In a spirit of ensemble, we finally combine network outputs to compute the probability of a given ROI image for determining the identity. Based on various experiments, we confirm that the proposed ensemble method is effective for user verification with palmprints and palm veins.

Medium to Long Range Wireless Video Transmission Scheme in 2.4GHz Band with Beamforming (빔 형성을 적용한 2.4GHz 대역 중장거리 영상 전송 무선 기술)

  • Paik, Junghoon;Kim, Namho;Jee, Minki
    • Journal of Broadcast Engineering
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    • v.23 no.5
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    • pp.693-700
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    • 2018
  • In this paper, we propose a wireless video transmission scheme, providing medium and long range communication in the 2.4GHz band with beamforming. With this scheme, it is shown that the transmission rate of 32Mbps and received signal power of -77dBm is achieved with 4 antennas of 5dBi and 16dBm transmit power at each antenna connection for the distance of 3.6km. The scheme also provides transmission distance of 20km for 10~12Mbps with the 4 omni-directional antennas of 5dBi.

BBA based Power Scaling Method in Cognitive Radio Technique for WPAN (WPAN을 위한 무선인지기술에서의 BBA 기반 전력할당기법)

  • Kim, Dae-Ik;Cho, Ju-Phil;Cha, Jae-Sang
    • Journal of Broadcast Engineering
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    • v.14 no.1
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    • pp.89-92
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    • 2009
  • In this paper, we discuss the BBA based power scaling scheme in cognitive radio technique for WPAN system. We focus on Cognitive Radio environment which is currently ongoing standard procedure and is able to focus on future communication and show the transmitted power scaling of CR user. We suggest the available communication method of CR user, while it is simultaneously satisfying both minimum interference of PU(Primary User) and possible communication of CR user. The method is using the BBA, and we show several merits in face of received SINR. and we prove that CR vary its transmit power while maintaining a guarantee of service to primary users.

Demosaicing Algorithm Using Directional Neighboring Pixels (근접 화소들의 방향성을 이용한 디모자이킹 알고리듬)

  • Kim, Hee-Chang;Jeong, Je-Chang
    • Journal of Broadcast Engineering
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    • v.14 no.6
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    • pp.742-748
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    • 2009
  • Most commercial digital still cameras use a single sensor array (e.g., CMOS or CCD) with color filter array (CFA) to reduce the cost and size. Since the image obtained with CFA has only one color value per pixel, the demosaicing is needed to acquire missing two color values. Although many demosaicing methods have been proposed, they still have artifacts such as rainbow and zippering artifact. In this paper, we propose the simple demosaicing algorithm using tendency of neighbor pixels with the enhanced weighting function. In the experimental results, our algorithm shows much better subjective qualities of the images than conventional demosaicing algorithm and improves objective qualities.

Point Cloud Registration Algorithm Based on RGB-D Camera for Shooting Volumetric Objects (체적형 객체 촬영을 위한 RGB-D 카메라 기반의 포인트 클라우드 정합 알고리즘)

  • Kim, Kyung-Jin;Park, Byung-Seo;Kim, Dong-Wook;Seo, Young-Ho
    • Journal of Broadcast Engineering
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    • v.24 no.5
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    • pp.765-774
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    • 2019
  • In this paper, we propose a point cloud matching algorithm for multiple RGB-D cameras. In general, computer vision is concerned with the problem of precisely estimating camera position. Existing 3D model generation methods require a large number of cameras or expensive 3D cameras. In addition, the conventional method of obtaining the camera external parameters through the two-dimensional image has a large estimation error. In this paper, we propose a method to obtain coordinate transformation parameters with an error within a valid range by using depth image and function optimization method to generate omni-directional three-dimensional model using 8 low-cost RGB-D cameras.