• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4292-4307
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• 2021

For the research field of night infrared surveillance video, the target imaging in the video is easily affected by the light due to the characteristics of the active infrared camera and the classical ViBe algorithm has some problems for moving target extraction because of background misjudgment, noise interference, ghost shadow and so on. Therefore, an improved ViBe algorithm (I-ViBe) for moving target extraction in night infrared surveillance video is proposed in this paper. Firstly, the video frames are sampled and judged by the degree of light influence, and the video frame is divided into three situations: no light change, small light change, and severe light change. Secondly, the ViBe algorithm is extracted the moving target when there is no light change. The segmentation factor of the ViBe algorithm is adaptively changed to reduce the impact of the light on the ViBe algorithm when the light change is small. The moving target is extracted using the region growing algorithm improved by the image entropy in the differential image of the current frame and the background model when the illumination changes drastically. Based on the results of the simulation, the I-ViBe algorithm proposed has better robustness to the influence of illumination. When extracting moving targets at night the I-ViBe algorithm can make target extraction more accurate and provide more effective data for further night behavior recognition and target tracking.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.7
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• pp.488-498
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• 2007

This paper presents a novel approach for representing the spatio-temporal topology of the camera network with overlapping and non-overlapping fields of view (FOVs) in Ubiquitous Smart Space (USS). The topology is determined by tracking moving objects and establishing object correspondence across multiple cameras. To track people successfully in multiple camera views, we used the Merge-Split (MS) approach for object occlusion in a single camera and the grid-based approach for extracting the accurate object feature. In addition, we considered the appearance of people and the transition time between entry and exit zones for tracking objects across blind regions of multiple cameras with non-overlapping FOVs. The main contribution of this paper is to estimate transition times between various entry and exit zones, and to graphically represent the camera topology as an undirected weighted graph using the transition probabilities.

• Journal of Satellite, Information and Communications
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• v.7 no.3
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• pp.116-120
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• 2012

There has been increased interest for building energy-saving for worldwide. There is continuing research on IT technology for efficient management of BEMS. Recently, It be able to control of LED and to maximize energy savings to the development of LED lighting technology. We propose the security image processing system to improve efficiency and we implement the real-time status monitoring system to surveil the object in the building energy management system. In this paper, we proposed the system of LED control using IP camera and Adaptive Gaussian Mixture Model for BEMS. We implement LED light control software on the based of the security camera image processing so the reliable controling based on the security camera is possible efficiently.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.17-22
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• 2009

DaVinci processors are popular media processors for implementing embedded multimedia applications. They support dual core architecture: ARM9 core for video I/O handling as well as system management and peripheral handling, and DSP C64+ core for effective digital signal processing. In this paper, we propose our efforts for optimal implementation of object tracking algorithm in DaVinci-based smart camera which is being designed and implemented by our laboratory. The smart camera in this paper is supposed to support object detection, object tracking, object classification and detection of intrusion into surveillance regions and sending the detection event to remote clients using IP protocol. Object tracking algorithm is computationally expensive since it needs to process several procedures such as foreground mask extraction, foreground mask correction, connected component labeling, blob region calculation, object prediction, and etc. which require large amount of computation times. Thus, if it is not implemented optimally in Davinci-based processors, one cannot expect real-time performance of the smart camera.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.7
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• pp.1056-1063
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• 2015

In this paper, we develop an interface for aerial photograph platform which consists of a quadrotor and a gimbal using the human body and the head posture. As quadrotors have been widely adopted in many industries such as aerial photography, remote surveillance, and maintenance of infrastructures, the demand of aerial video and photograph has been increasing remarkably. Stick type remote controllers are widely used to control a quadrotor, but this method is not an intuitive way of controlling the aerial vehicle and the camera simultaneously. Therefore, a new interface which controls the serial photograph platform is presented. The presented interface uses the human head movement measured by head-mounted display as a reference for controlling the camera angle, and the human body posture measured from Kinect for controlling the attitude of the quadrotor. As the image captured by the camera is displayed on the head-mounted display simultaneously, the user can feel flying experience and intuitively control the quadrotor and the camera. Finally, the performance of the developed system shown to verify the effectiveness and superiority of the presented interface.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.667-670
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• 2005

As security and surveillance have become the center of interest, remote controlled CCTV(Closed-Circuit Television) market has been formed while rapid development of digital image compression technology and Internet triggered the advent of web cameras. The characteristic of web camera is that it can provide users with higher quality image than CCTV at any place where Internet access is available. However, As for the system administrator, the existing web camera have disadvantage in that they allows users only. who are connected to the server of the web camera, to see the image from it. In this paper, in order to make up for this defect, designed multi-vision interface showing multi images on single screen and, for the purpose of the improvement in efficiency, the functions of saving images and of scheduling the time to save the images.

• Journal of Veterinary Science
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• v.23 no.1
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• pp.17.1-17.10
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• 2022

Background: Inspection of livestock farms using surveillance cameras is emerging as a means of early detection of transboundary animal disease such as African swine fever (ASF). Object tracking, a developing technology derived from object detection aims to the consistent identification of individual objects in farms. Objectives: This study was conducted as a preliminary investigation for practical application to livestock farms. With the use of a high-performance artificial intelligence (AI)-based 3D depth camera, the aim is to establish a pathway for utilizing AI models to perform advanced object tracking. Methods: Multiple crossovers by two humans will be simulated to investigate the potential of object tracking. Inspection of consistent identification will be the evidence of object tracking after crossing over. Two AI models, a fast model and an accurate model, were tested and compared with regard to their object tracking performance in 3D. Finally, the recording of pig pen was also processed with aforementioned AI model to test the possibility of 3D object detection. Results: Both AI successfully processed and provided a 3D bounding box, identification number, and distance away from camera for each individual human. The accurate detection model had better evidence than the fast detection model on 3D object tracking and showed the potential application onto pigs as a livestock. Conclusions: Preparing a custom dataset to train AI models in an appropriate farm is required for proper 3D object detection to operate object tracking for pigs at an ideal level. This will allow the farm to smoothly transit traditional methods to ASF-preventing precision livestock farming.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.9
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• pp.120-125
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• 2016

For the purpose of protecting personal property and lives from incidents, accidents, and threats such as terrorism, video surveillance equipment has been installed and operates in many places. Video surveillance technology has gradually developed into high-quality, high-definition equipment, and a lot of products have been launched. However, closed circuit television (CCTV) equipment for security purposes can invade a person's privacy. In this paper, we propose a way to protect personal video images using meta-data in an intelligent Internet protocol (IP) camera. We designed the system to mask personal video information from meta-data, define the method of image-information access according to user privileges, and show how to utilize the meta-data during storage and recorded data searches. The suggested system complies with guidelines for CCTV installation and operation from Korea's Ministry of the Interior. Installed on only a single server so far, due to the limitations and technical difficulties of hardware performance, it has been difficult to find a method that can be applied to personal image information using real-time protection techniques. Applying the method proposed in this paper can satisfy the guidelines, reduce server costs, and reduce system complexity.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.15-18
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• 2007

Identification of humans from multiple view points is an important task for surveillance and security purposes. For optimal performance the system should use the maximum information available from sensors. Multimodal biometric systems are capable of utilizing more than one physiological or behavioral characteristic for enrollment, verification, or identification. Since gait alone is not yet established as a very distinctive feature, this paper presents an approach to fuse face and gait for identification. In this paper we will use the single camera case i.e. both the face and gait recognition is done using the same set of images captured by a single camera. The aim of this paper is to improve the performance of the system by utilizing the maximum amount of information available in the images. Fusion is considered at decision level. The proposed algorithm is tested on the NLPR database.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.1
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• pp.7-13
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• 2015

Unmanned air vehicles (UAVs) are getting popular not only as a private usage for the aerial photograph but military usage for the surveillance, reconnaissance and supply missions. For an UAV to successfully achieve these kind of missions, geolocation (localization) must be implied to track an interested target or fly by reference. In this research, we adopted multi-sensor fusion (MSF) algorithm to increase the accuracy of the geolocation and verified the algorithm using two multicopter UAVs. One UAV is equipped with an optical camera, and another UAV is equipped with an optical camera and a laser range finder. Throughout the experiment, we have obtained measurements about a fixed ground target and estimated the target position by a series of coordinate transformations and sequential Kalman filter. The result showed that the MSF has better performance in estimating target location than the case of using single sensor. Moreover, the experimental result implied that multi-sensor geolocation algorithm is able to have further improvements in localization accuracy and feasibility of other complicated applications such as moving target tracking and multiple target tracking.