• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2012.07a
• /
• pp.298-301
• /
• 2012

This paper presents a graph-based method of detecting and tracking moving objects in H.264/SVC bitstreams for video surveillance applications that makes use the information from spatial base and enhancement layers of the bitstreams. In the base layer, segmentation of real moving objects are first performed using a spatio-temporal graph by removing false detected objects via graph pruning and graph projection, followed by graph matching to precisely identify the real moving objects over time even under occlusion. For the accurate detection and reliable tracking of moving objects in the enhancement layer, as well as saving computational complexity, the identified block groups of the real moving objects in the base layer are then mapped to the enhancement layer to provide accurate and efficient object detection and tracking in the bitstreams of higher resolution. Experimental results show the proposed method can produce reliable results with low computational complexity in both spatial layers of H.264/SVC test bitstreams.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2011.07a
• /
• pp.99-101
• /
• 2011

본 논문에서는 WiMAX 의 신호세기(CINR: Carrier to Interference + Noise Ratio)의 변화와 예측 방법에 대해 연구한다. WiMAX 와 같은 무선 네트워크에서는 신호세기가 불규칙하게 변화하기 때문에 비디오 스트리밍시 에러나 지연이 발생할 수 있다. CINR 은 클라이언트 측의 가용 대역폭을 결정하는 중요한 요소이다. 하지만 기존의 RTCP(Real-time Transport Control Protocol)를 이용한 비트율 제어는 RTT(Round Trip time), PLR(Packet Loss Rate) 등의 정보를 사용하기 때문에 부정확하거나 지연이 발생될 수 있다. 이를 보완하기 위한 CINR 을 직접 비트율 제어에 사용하는 방법에 대해 연구하기에 앞서, 본 논문에서는 CINR 을 분석하고 미래의 값을 예측하는 방법에 대해 연구한다. 본 논문의 분석을 통해 CINR 의 예측을 비교적 정확하게 수행할 수 있다면 앞으로의 가용 대역폭을 비교적 정확하게 예측할 수 있고 효율적인 비디오 스트리밍 시스템을 제안할 수 있다.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.20 no.43
• /
• pp.91-97
• /
• 1997

The objective of a traffic management system is to promote safe driving, low pollution, short travel time, and optimized traffic flow by naturally distributing the flow of traffic through the use of suitable telecommunications media. Such traffic management systems will be improved by integrating dynamic traffic data and two-way communication media because cars can work as sensors. The purpose of this paper is to help organizations trying to select the correct telecommunications media for minimal-cost investment options without loss of functionality. The wireless communications for an intelligent transportation system (ITS) are introduced in this paper. We describe which kind of telecommunication media are suitable. FM broadcast type media or cellular phone can be recommended to provide real time traffic and roadway conditions in the first stage of ITS, because existing broadcast base station or cellular network facilities can be used. It is expected that cellular radio network or satellites are used for communication. Finally, the strategy and deployment plan of an ITS are described based on selections of telecommunication media in Korea.

• Journal of Broadcast Engineering
• /
• v.19 no.6
• /
• pp.942-956
• /
• 2014

This paper proposes a real-time hand pose tracking method using a monocular RGB camera. Hand tracking has high ambiguity since a hand has a number of degrees of freedom. Thus, to reduce the ambiguity the proposed method adopts the step-by-step estimation scheme: a palm pose estimation, a finger yaw motion estimation, and a finger pitch motion estimation, which are performed in consecutive order. Assuming a hand to be a plane, the proposed method utilizes a planar hand model, which facilitates a hand model regeneration. The hand model regeneration modifies the hand model to fit a current user's hand, and improves robustness and accuracy of the tracking results. The proposed method can work in real-time and does not require GPU-based processing. Thus, it can be applied to various platforms including mobile devices such as Google Glass. The effectiveness and performance of the proposed method will be verified through various experiments.

• Journal of Broadcast Engineering
• /
• v.21 no.6
• /
• pp.861-877
• /
• 2016

This paper first discusses the disadvantages of the existing CamShift Algorithm for real time face tracking, and then proposes a new Camshift Algorithm that performs better than the existing algorithm. The existing CamShift Algorithm shows unstable tracking when tracing similar colors in the background of objects. This drawback of the existing CamShift is resolved by using Kinect’s pixel-by-pixel depth information and the Skin Detection algorithm to extract candidate skin regions based on HSV color space. Additionally, even when the tracking object is not found, or when occlusion occurs, the feature point-based matching algorithm makes it robust to occlusion. By applying the improved CamShift algorithm to face tracking, the proposed real-time face tracking algorithm can be applied to various fields. The results from the experiment prove that the proposed algorithm is superior in tracking performance to that of existing TLD tracking algorithm, and offers faster processing speed. Also, while the proposed algorithm has a slower processing speed than CamShift, it overcomes all the existing shortfalls of the existing CamShift.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.32 no.12B
• /
• pp.758-766
• /
• 2007

IStreaming services with a client-server architecture have scalability problem because a server cannot accomodate clients more than its processing capability. This paper introduces a case study for implementing H.264 streaming system based on P2P architecture in order to provide scalable and stable broadcast streaming services over the internet. The prototype system called OmniCast264 consists of the H.264 encoding server, the streaming server, the proxy server, and peer nodes. The proxy server dynamically manages placement of the peer nodes on the P2P network. Omnicast264 has the concepts of distributed streaming loads, real-time playback, error-robustness and modularity. Thus, it can provide large-scale broadcast streaming services. Finally, we have built P2P streaming systems with 12 PCs connected serially or in parallel. The experiment shows that OmniCast264 can provide real-time playback.

• Journal of Broadcast Engineering
• /
• v.16 no.5
• /
• pp.738-749
• /
• 2011

In this paper, we study QoS(Quality of Service) control protocols and the effect using MAC/PHY parameters of client device in mobile network. We proposes the way of controling the bit-rate by estimating the channel condition of the client with measured MAC/PHY parameters which is sent from the client. With the proposed method, more accurate available bit-rate can be estimated compared to conventional protocol, RTCP(Real-time Transport Control Protocol). The accurate bit-rate estimation can decrease wasted bit-rate and transport delay. In the result of the advantages, the transported video quality can be enhanced. In this paper, we show the effects of enhancement using client's the field data measured in WiMAX.

• Journal of Broadcast Engineering
• /
• v.7 no.1
• /
• pp.2-9
• /
• 2002

Recently. VR( Virtual Reality) applications such as virtual studio and virtual character are wifely used In TV programs. and AR( Augmented Reality) applications are also belong taken an interest increasingly. This paper introduces a virtual screen system. which Is a new AR application for broadcasting. The virtual screen system is a real-time video augmentation system by tracking a chroma-patterned moving panel. We haute recently developed a virtual screen system.'K-vision'. Our system enables the user to hold and morse a simple panel on which live video, pictures of 3D graphics images can appear. All the Images seen on the panel change In the correct perspective, according to movements of the camera and the user holding the panel, in real-time. For the purpose of tracking janet. we use some computer vision techniques such as blob analysis and feature tracking. K-vision can work well with any type of camera. requiring no special add-ons. And no need for sensor attachments to the panel. no calibration procedures required. We are using K-vision in some TV programs such as election. documentary and entertainment.

• Journal of Broadcast Engineering
• /
• v.26 no.2
• /
• pp.132-142
• /
• 2021

The purpose of this study is to present an effective methodology that can measure heart rate, heart rate variability, oxygen saturation, respiration rate, mental stress level, and blood pressure using mobile front camera that can be accessed most in real life. Face recognition was performed in real-time using Blaze Face to acquire facial image data, and the forehead was designated as ROI (Region Of Interest) using feature points of the eyes, nose, and mouth, and ears. Representative values for each channel of the ROI were generated and aligned on the time axis to measure vital signs. The vital signs measurement method was based on Fourier transform, and noise was removed and filtered according to the desired vital signs to increase the accuracy of the measurement. To verify the results, vital signs measured using facial image data were compared with pulse oximeter contact sensor, and TI non-contact sensor. As a result of this work, the possibility of extracting a total of six vital signs (heart rate, heart rate variability, oxygen saturation, respiratory rate, stress, and blood pressure) was confirmed through facial images.

• Journal of Broadcast Engineering
• /
• v.25 no.6
• /
• pp.1004-1012
• /
• 2020

We present a novel content-preserving seam estimation algorithm for real-time high-resolution video stitching. Seam estimation is one of the fundamental steps in image/video stitching. It is to minimize visual artifacts in the transition areas between images. Typical seam estimation algorithms are based on optimization methods that demand intensive computations and large memory. The algorithms, however, often fail to avoid objects and results in cropped or duplicated objects. They also lack temporal consistency and induce flickering between frames. Hence, we propose an efficient and temporarily-consistent seam estimation algorithm that utilizes a straight line. The proposed method also uses convolutional neural network-based instance segmentation to locate seam at out-of-objects. Experimental results demonstrate that the proposed method produces visually plausible stitched videos with minimal visual artifacts in real-time.