• Journal of the Korean Society of Industry Convergence
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• v.22 no.1
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• pp.39-45
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• 2019

We propose an active color model based method for tracking motions of multiple human using a networked multiple-camera system in IoT space as a human-robot coexistent system. An IoT space is a space where many intelligent devices, such as computers and sensors(color CCD cameras for example), are distributed. Human beings can be a part of IoT space as well. One of the main goals of IoT space is to assist humans and to do different services for them. In order to be capable of doing that, IoT space must be able to do different human related tasks. One of them is to identify and track multiple objects seamlessly. In the environment where many camera modules are distributed on network, it is important to identify object in order to track it, because different cameras may be needed as object moves throughout the space and IoT space should determine the appropriate one. This paper describes appearance based unknown object tracking with the distributed vision system in IoT space. First, we discuss how object color information is obtained and how the color appearance based model is constructed from this data. Then, we discuss the global color model based on the local color information. The process of learning within global model and the experimental results are also presented.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.221-226
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• 2009

Not many years ago, people found the contemporary technology expensive and difficult to use in collaborative type of meetings. Today, with the technology advanced to high standards and accessible at cheaper price, its adaption is becoming more and more ubiquitous with wide range of applications. Today's meeting rooms are not just plain old telephone systems with microphones and speakers. Today's meeting rooms are smart and intelligent. They can identify the participants; they can provide natural view of remote participants; they can proactively manage resources for collaboration and so on. More effective collaboration is possible with deployment of devices like high-definition cameras, advanced displays, sensors, gigabit networks, trackers, pointers, and high-end audio devices. Devices alone are not enough in the meeting rooms. We need software infrastructure to manage the devices and meeting contexts. One such software infrastructure is SMeet, a Smart Meeting space, which we have developed to provide an effective multi-party remote collaboration environment. Networked display systems are used in such advanced collaboration environment for better visualization. In this paper we discuss a novel approach to control and manage networked display systems in SMeet environment.

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.4
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• pp.241-253
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• 2006

In modem societies, a monitoring system is required to automatically detect and track persons from several cameras scattered in a wide area. Combining multiple cameras with non-overlapping views and a tracking technique, we propose a method that tracks automatically the target persons in one camera and transfers the tracking information to other networked cameras through a server. So the proposed method tracks thoroughly the target persons over the cameras. In this paper, we use a person model to detect and distinguish the corresponding person and to transfer the person's tracking information. A movement of the tracked persons is defined on FOV lines of the networked cameras. The tracked person has 6 statuses. The proposed system was experimented in several indoor scenario. We achieved 91.2% in an averaged tracking rate and 96% in an averaged status rate.

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.107-113
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• 2019

Along with the development of IOT, the number of people using IOT devices has enormously increased and the IOT era has come. Especially, people using the IP cameras among Internet devices have been drastically increasing. It is because the IP cameras are well networked and comparatively cheap compared with CCTVs, and they can also be monitored and controlled in real time through PCs and smart phones for the purposes of general theft prevention and shop surveillance. However, due to the user's serious lack of security awareness and the fact that anyone can easily hack only with simple hacking tools and hacking sites information, security crimes that exploit those have been increasing as well. Therefore, this paper describes how easily the IP cameras can be hacked in the era of IOT, what kind of security incidents occurred, and also suggests possible government measures and new technical solutions to those problems.

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.45-52
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• 2014

The Ubiquitous-City (U-City) is a smart or intelligent city to satisfy human beings' desire to enjoy IT services with any device, anytime, anywhere. It is a future city model based on Internet of everything or things (IoE or IoT). It includes a lot of video cameras which are networked together. The networked video cameras support a lot of U-City services as one of the main input data together with sensors. They generate huge amount of video information, real big data for the U-City all the time. It is usually required that the U-City manipulates the big data in real-time. And it is not easy at all. Also, many times, it is required that the accumulated video data are analyzed to detect an event or find a figure among them. It requires a lot of computational power and usually takes a lot of time. Currently we can find researches which try to reduce the processing time of the big video data. Cloud computing can be a good solution to address this matter. There are many cloud computing methodologies which can be used to address the matter. MapReduce is an interesting and attractive methodology for it. It has many advantages and is getting popularity in many areas. Video cameras evolve day by day so that the resolution improves sharply. It leads to the exponential growth of the produced data by the networked video cameras. We are coping with real big data when we have to deal with video image data which are produced by the good quality video cameras. A video surveillance system was not useful until we find the cloud computing. But it is now being widely spread in U-Cities since we find some useful methodologies. Video data are unstructured data thus it is not easy to find a good research result of analyzing the data with MapReduce. This paper presents an analyzing system for the video surveillance system, which is a cloud-computing based video data management system. It is easy to deploy, flexible and reliable. It consists of the video manager, the video monitors, the storage for the video images, the storage client and streaming IN component. The "video monitor" for the video images consists of "video translater" and "protocol manager". The "storage" contains MapReduce analyzer. All components were designed according to the functional requirement of video surveillance system. The "streaming IN" component receives the video data from the networked video cameras and delivers them to the "storage client". It also manages the bottleneck of the network to smooth the data stream. The "storage client" receives the video data from the "streaming IN" component and stores them to the storage. It also helps other components to access the storage. The "video monitor" component transfers the video data by smoothly streaming and manages the protocol. The "video translator" sub-component enables users to manage the resolution, the codec and the frame rate of the video image. The "protocol" sub-component manages the Real Time Streaming Protocol (RTSP) and Real Time Messaging Protocol (RTMP). We use Hadoop Distributed File System(HDFS) for the storage of cloud computing. Hadoop stores the data in HDFS and provides the platform that can process data with simple MapReduce programming model. We suggest our own methodology to analyze the video images using MapReduce in this paper. That is, the workflow of video analysis is presented and detailed explanation is given in this paper. The performance evaluation was experiment and we found that our proposed system worked well. The performance evaluation results are presented in this paper with analysis. With our cluster system, we used compressed $1920{\times}1080(FHD)$ resolution video data, H.264 codec and HDFS as video storage. We measured the processing time according to the number of frame per mapper. Tracing the optimal splitting size of input data and the processing time according to the number of node, we found the linearity of the system performance.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.1
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• pp.39-46
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• 2006

We propose an global color model based method for tracking motions of multiple human using a networked multiple-camera system in intelligent space as a human-robot coexistent system. An intelligent space is a space where many intelligent devices, such as computers and sensors(color CCD cameras for example), are distributed. Human beings can be a part of intelligent space as well. One of the main goals of intelligent space is to assist humans and to do different services for them. In order to be capable of doing that, intelligent space must be able to do different human related tasks. One of them is to identify and track multiple objects seamlessly. In the environment where many camera modules are distributed on network, it is important to identify object in order to track it, because different cameras may be needed as object moves throughout the space and intelligent space should determine the appropriate one. This paper describes appearance based unknown object tracking with the distributed vision system in intelligent space. First, we discuss how object color information is obtained and how the color appearance based model is constructed from this data. Then, we discuss the global color model based on the local color information. The process of learning within global model and the experimental results are also presented.

• The Journal of the Korea Contents Association
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• v.16 no.9
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• pp.329-338
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• 2016

Internet of Things (IoTs) technology makes every things in physical world being digitalized and communicated with each other. The technology is emerging as a new paradigm and is expected to provide a convenient and effective life. However, for the successful realization of the IoT technologies, IoT security issues are an important prerequisite, and particularly the privacy protection is expected to become more important in view of object communication directively related with human. In this paper we describe for the security and privacy threats in IoT environment and introduce the shodan (a legitimate search engine that finds backdoor routers, switches, webcams, IoT devices connected to the Internet etc.) that can expose the security and privacy problems. Lastly, we compare the privacy threats through real-world case study of network cameras currently in use and finally derive the countermeasures for the threats.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.4
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• pp.293-298
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• 2006

In this paper, a sensor fusion based robot navigation method for the autonomous control of a miniature human interaction robot is presented. The method of navigation blends the optimality of the Fuzzy Neural Network(FNN) based control algorithm with the capabilities in expressing knowledge and learning of the networked Intelligent Robotic Space(IRS). States of robot and IR space, for examples, the distance between the mobile robot and obstacles and the velocity of mobile robot, are used as the inputs of fuzzy logic controller. The navigation strategy is based on the combination of fuzzy rules tuned for both goal-approach and obstacle-avoidance. To identify the environments, a sensor fusion technique is introduced, where the sensory data of ultrasonic sensors and a vision sensor are fused into the identification process. Preliminary experiment and results are shown to demonstrate the merit of the introduced navigation control algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.868-871
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• 2009

We propose an global color model based method for tracking motions of multiple human using a networked multiple-camera system in intelligent space as a human-robot coexistent system. An intelligent space is a space where many intelligent devices, such as computers and sensors(color CCD cameras for example), are distributed. Human beings can be a part of intelligent space as well. One of the main goals of intelligent space is to assist humans and to do different services for them. In order to be capable of doing that, intelligent space must be able to do different human related tasks. One of them is to identify and track multiple objects seamlessly.

• Journal of Broadcast Engineering
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• v.13 no.6
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• pp.930-940
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• 2008

This paper proposes a prototype realization of multi-view HD video transport system with synchronized multiplexing over IP networks. The proposed synchronized multiplexing considers the synchronization during video acquisition and the multiplexing for the interactive view-selection during transport. For the synchronized acquisition from multiple HDV camcorders through IEEE 1394 interface, we estimate the timeline differences among MPEG-2 compressed video streams by using global time of network between the cameras and a server and correct timelines of video streams by changing the time stamp of the MPEG-2 system stream. Also, we multiplex a selected number of acquired HD views at the MPEG-2 TS (transport stream) level for the interactive view-selection during transport. Thus, with the proposed synchronized multiplexing scheme, we can display synchronized HD view.