• Journal of Communications and Networks
• /
• v.14 no.3
• /
• pp.286-295
• /
• 2012

To meet the increased demand of video-on-demand (VoD) services, peer-to-peer (P2P) mesh-based multiple video approaches have been recently proposed, where each peer is able to find a video segment interested without resort to the video server. However, they have not considered the constraint of the server's upload bandwidth and the fairness between upload and download amounts at each peer. In this paper, we propose a novel P2P VoD streaming system, named peer cache adaptation (PECAN) where each peer adjusts its cache capacity adaptively to meet the server's upload bandwidth constraint and achieve the fairness. For doing so, we first propose a new cache replacement algorithm that designs the number of caches for a segment to be proportional to its popularity. Second, we mathematically prove that if the cache capacity of a peer is proportional to its segment request rate, the fairness between upload and download amounts at each peer can be achieved. Third, we propose a method that determines each peer's cache capacity adaptively according to the constraint of the server's upload bandwidth. Against the proposed design objective, some selfish peers may not follow our protocol to increase their payoff. To detect such peers, we design a simple distributed reputation and monitoring system. Through simulations, we show that PECAN meets the server upload bandwidth constraint, and achieves the fairness well at each peer. We finally verify that the control overhead in PECAN caused by the search, reputation, and monitoring systems is very small, which is an important factor for real deployment.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.13 no.1
• /
• pp.169-174
• /
• 2018

There are many CCTV cameras connected to the video surveillance and monitoring center for the safety of citizens, and it is difficult for a few monitoring agents to monitor many channels of videos. In this paper, we propose an intelligent video surveillance system utilizing a safety map to efficiently monitor many channels of CCTV camera videos. The safety map establishes the frequency of crime occurrence as a database, expresses the degree of crime risk and makes it possible for agents of the video surveillance center to pay attention when a woman enters the crime risk area. The proposed gender classification method is processed in the order of pedestrian detection, tracking and classification with deep training. The pedestrian detection and tracking uses Adaboost algorithm and probabilistic data association filter, respectively. In order to classify the gender of the pedestrian, relatively simple AlexNet is applied to determine gender. Experimental results show that the proposed gender classification method is more effective than the conventional algorithm. In addition, the results of implementation of intelligent video security system combined with safety map are introduced.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.12
• /
• pp.141-149
• /
• 2022

In this paper, we propose a design of CCTV enlcosure record management system based on blockchain. Since CCTV video records are transferred to the control center through enclosure, it is very important to manage the enclosure to prevent modulation and damage of the video records. Recently, a smart enclosure monitoring system with real-time remote monitoring and opening and closing state management functions is used to manage CCTV enclosures, but there is a limitation to securing the safety of CCTV video records. The proposed system detect modulated record and recover the record through hash value comparison by distributed stored record in the blockchain. In addition, the integrity verification API is provided to ensure the integrity of enclosure record received by the management server. In order to verify the effectiveness of the system, the integrity verification accuracy and elapsed time were measured through experiments. As a result, the integrity of enclosure record (accuracy: 100%) was confirmed, and it was confirmed that the elapsed time for verification (average: 73 ms) did not affect monitoring.

• Proceedings of the KIEE Conference
• /
• 2003.11b
• /
• pp.195-198
• /
• 2003

Monitoring and analyzing people in video images are important and attract attention from many researchers in computer vision field. In this paper, we propose a new technique by which people overlapped one another in an image can be extracted and counted. After extracting moving people from video images as foreground, their heads are searched by Hough Transform inside the foreground. Since heads are comparatively stable in spite of motion in video images, semicircles along the head tops can be important features to be found in an edge map. In our experiment, the technique successfully separated people who existed at the same vertical positions, which was Impossible by existing techniques. Meanwhile, it showed high dependency on edge information and false results were obtained when the rather were rather incomplete.

• Korean Journal of Geomatics
• /
• v.3 no.2
• /
• pp.93-98
• /
• 2004

Fast urbanization and industrialization have resulted in rapid changes in the urban environment. For effective monitoring and management of these changes, a new surveying methodology that is more inexpensive and timely than the conventional remote sensing system if required. This paper proposes an unmanned airship videographic system capable of acquiring stable video. In addition, it presents approaches to constructing a prototype facilities management system based on VideoGIS, which links GIS functions and video data to provide actual spatiotemporal information.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.28 no.4
• /
• pp.403-411
• /
• 2010

This research demonstrates a 3D virtual visualization of urban environment and video fusion for effective damage prevention and surveillance system using open standard. We present the visualization and interaction simulation method to increase the situational awareness and optimize the realization of environmental monitoring through the CCTV video and 3D virtual environment. New camera prototype was designed based on the camera frustum view model to project recorded video prospectively onto the virtual 3D environment. The demonstration was developed by the X3D, which is royalty-free open standard and run-time architecture, and it offers abilities to represent, control and share 3D spatial information via the internet browsers.

• Journal of Advanced Information Technology and Convergence
• /
• v.10 no.2
• /
• pp.125-138
• /
• 2020

Due to the development of camera technology, the cost of producing time-lapse video has been reduced, and time-lapse videos are being applied in many fields. Time-lapse video is created using images obtained by shooting for a long time at long intervals. In this paper, we propose a method to improve the quality of time-lapse videos monitoring the changes in plants. Considering the characteristics of time-lapse video, we propose a method of separating the desired and unnecessary objects and removing unnecessary elements. The characteristic of time-lapse videos that we have noticed is that unnecessary elements appear intermittently in the captured images. In the proposed method, noises are removed by applying a codebook background modeling algorithm to use this characteristic. Experimental results show that the proposed method is simple and accurate to find and remove unnecessary elements in time-lapse videos.

• Journal of the Korea Computer Industry Society
• /
• v.6 no.3
• /
• pp.509-518
• /
• 2005

The RMS(Remote Monitoring System) is generalized to adopt in many automatic system by progress of industrial and technical growth. RMS has been developed from simple status monitoring system to realtime control system with multimedia interface. This study is to design and develop monitoring system that client is able to monitor and control target system on web browser. The RMS is consist of 4 functional modes, which is monitoring mode, control mode, setup mode and video mode. Monitoring mode is to observe remote target system with realtime on web browser. Control mode is to change target system status in monitoring mode. Setup mode is to change system variable in control mode. Video mode is to monitor target system environment visually by web camera. This RMS is easy to access and manage target system, and so useful to monitor remote automatic system and closing site.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.36 no.2A
• /
• pp.114-126
• /
• 2011

Video streaming over wireless multi-hop networks(WMNs) contains the following challenges from channel fading and variable bandwidth of wireless channel, and it cause degradation of video streaming performance. To overcome the challenges, currently, WMNs can use Forward Error Correction (FEC) mechanism. In WMNs, traditional FEC schemes, E2E-FEC and HbH-FEC, for video streaming are applied, but it has long transmission delay, high computational complexity and inefficient usage of resource. Also, to distinguish network status in streaming path, it has limitation. In this paper, we propose monitoring-based coordination of network-adaptive hop-to-end(H2E) FEC scheme. To enable proposed scheme, we apply a centralized coordinator. The coordinator has observing overall monitoring information and coordinating H2E-FEC mechanism. Main points of H2E-FEC is distinguishing operation range as well as selecting FEC starting node and redundancy from monitored results in coordination. To verify the proposed scheme, we perform extensive experiment over the OMF(Orbit Measurement Framework) and IEEE 802.1la-based multi-hop WMN testbed, and we carry out performance improvement, 17%, from performance comparison by existing FEC scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.9
• /
• pp.4572-4586
• /
• 2019

Mobile Edge Computing (MEC) and Information-Centric Networking (ICN) are essential network architectures for the future Internet. The advantages of MEC and ICN such as computation and storage capabilities at the edge of the network, in-network caching and named-data communication paradigm can greatly improve the quality of video streaming applications. However, the packet loss in wireless network environments still affects the video streaming performance and the existing loss recovery approaches in ICN does not exploit the capabilities of MEC. This paper proposes a Deep Learning based Loss Recovery Mechanism (DL-LRM) for video streaming over MEC based ICN. Different with existing approaches, the Forward Error Correction (FEC) packets are generated at the edge of the network, which dramatically reduces the workload of core network and backhaul. By monitoring network states, our proposed DL-LRM controls the FEC request rate by deep reinforcement learning algorithm. Considering the characteristics of video streaming and MEC, in this paper we develop content caching detection and fast retransmission algorithm to effectively utilize resources of MEC. Experimental results demonstrate that the DL-LRM is able to adaptively adjust and control the FEC request rate and achieve better video quality than the existing approaches.