• Journal of Digital Convergence
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• v.11 no.10
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• pp.359-366
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• 2013

Due to the development and market expansion of image analysis and recognition technology, video security such as CCTV cameras and digital storage devices, are required for real-time monitoring systems and intelligent video security systems. This includes the development of more advanced technologies. A rotatable PTZ camera, in a CCTV camera system, has a zoom function so you can acquire a precise picture. However it can cause blind spots, and can not monitor two or more moving objects at the same time. This study concerns, the intelligent tracking of multiple moving objects, CCTV systems, and methods of video surveillance. An intelligent video surveillance system is proposed. It can accurately shoot broad areas and track multiple objects at the same time, much more effectively than using one fixed camera for an entire area or two or more PTZ cameras.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.3
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• pp.41-49
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• 2010

Recently, RFID systems are spreading in various industrial areas faster but cause some serious problems of information security because of its unstable wireless communication. Moreover, traditional RFID systems have a restriction that one tag per each application object. This restriction deteriorates their usability because it is difficult to distinguish many tags without some kind of effort. Therefore, efficient information sharing of objects based on information security has to be studied for more spreading of RFID technologies. In this paper, we design a new RFID tag structure for supporting multiple objects which can be shared by many different RFID applications. We also design an encryption/decryption algorithm to protect the identifying information of objects stored in our tag structure. This algorithm is a light revision of the existing SEED algorithm which can be operated in RFID tag environment. To evaluate the performance of our algorithm, we measure the encryption and decryption times of this algorithm and compare the results with those of the original SEED algorithm.

• Proceedings of the Optical Society of Korea Conference
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• 2009.02a
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• pp.167-168
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• 2009

We propose a new computing method for Fourier hologram of 3D objects captured by lens array. Fourier hologram of the two objects which positioned at different distances can be calculated using multiple orthographic view images. The size of the Fourier hologram is in proportion to the number of the orthographic view images. By repeating the orthographic view images, the size of the Fourier hologram can be increased. The principle is verified by numerically reconstructing the hologram which is synthesized from the orthographic images captured optically.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.721-725
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• 2004

Multiple-count problem is occurred when rectangle objects span across several buckets. The Cumulative Density (CD) histogram is a technique which solves multiple-count problem by keeping four sub-histograms corresponding to the four points of rectangle. Although it provides exact results with constant response time, there is still a considerable issue. Since it is based on a query window which aligns with a given grid, a number of errors may be occurred when it is applied to real applications. In this paper, we proposed selectivity estimation techniques using the generalized cumulative density histogram based on two probabilistic models: (1) probabilistic model which considers the query window area ratio, (2) probabilistic model which considers intersection area between a given grid and objects. In order to evaluate the proposed methods, we experimented with real dataset and experimental results showed that the proposed technique was superior to the existing selectivity estimation techniques. The proposed techniques can be used to accurately quantify the selectivity of the spatial range query on rectangle objects.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1524-1529
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• 2005

Particle filter is a kind of conditional density propagation model. Its similar characteristics to both selection and mutation operator of evolutionary strategy (ES) due to its Bayesian inference rule structure, shows better performance than any other tracking algorithms. When a new object is entering the region of interest, particle filter sets which have been swarming around the existing objects have to move and track the new one instantaneously. Moreover, there is another problem that it could not track multiple objects well if they were moving away from each other after having been overlapped. To resolve reinitialization problem, we use competitive-AVQ algorithm of neural network. And we regard interfarme difference (IFD) of background images as potential field and give priority to the particles according to this IFD to track multiple objects independently. In this paper, we showed that the possibility of real-time object tracking as intelligent interfaces by simulating the deformable contour particle filters.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.103.5-103
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• 2001

This paper presents a visual feedback system that controls a micromanipulator using multiple microscopic vision information. The micromanipulation stations basically have optical microscope. However the single field-of-view of optical microscope essentially limits the workspace of the micromanipulator and low dept-of-field makes it difficult to handle 3D-shaped micro objects. The system consists of a stereoscopic microscope, three CCD cameras, the micromanipulator and personal computer. The use of stereoscopic microscope which has long working distance and high depth-of-field with selective field-of-view improves the recognizability of 3D-shaped micro objects and provides a method for overcoming several essential limitations in micromanipulation. Thus, visual feedback information is very important in handling micro objects for overcoming those limitations and provides a mean for the ...

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.11
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• pp.952-959
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• 2016

This paper proposes a novel indoor positioning system (IPS) that uses a calibrated camera sensor network and dense 3D map information. The proposed IPS information is obtained by generating a bird's-eye image from multiple camera images; thus, our proposed IPS can provide accurate position information when objects (e.g., the mobile robot or pedestrians) are detected from multiple camera views. We evaluate the proposed IPS in a real environment with moving objects in a wireless camera sensor network. The results demonstrate that the proposed IPS can provide accurate position information for moving objects. This can improve the localization performance for mobile robot operation.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1347-1349
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• 1996

Most real image sequences contain multiple moving objects or multiple motions. In this paper, we segmented the moving objects with optical flow. Motion estimation by this method can estimate and compress the image sequences better than other methods such as block matching method. And, especially, we can make new image sequences by synthesizing the segmented objects. But, it takes too much time for motion estimation. And, it is not easy for a hardware implementation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.5
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• pp.697-704
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• 2003

In this paper, the visual tracking system for arbitrary shaped moving object is proposed. The established tracking system can be divided into model based method that needs previous model for target object and image based method that uses image feature. In the model based method, the reliable tracking is possible, but simplification of the shape is necessary and the application is restricted to definite target mod el. On the other hand, in the image based method, the process speed can be increased, but the shape information is lost and the tracking system is sensitive to image noise. The proposed tracking system is composed of the extraction process that recognizes the existence of moving object and tracking process that extracts dynamic characteristics and shape information of the target objects. Specially, active contour model is used to effectively track the object that is undergoing shape change. In initializatio n process of the contour model, the semi-automatic operation can be avoided and the convergence speed of the contour can be increased by the proposed effective initialization method. Also, for the efficient solution of the correspondence problem in multiple objects tracking, the variation function that uses the variation of position structure in image frame and snake energy level is proposed. In order to verify the validity and effectiveness of the proposed tracking system, real time tracking experiment for multiple moving objects is implemented.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.11
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• pp.95-101
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• 1999

In this paper, we propose an adaptive method of tracking multiple moving objects using contour and features in surrounding conditions. We use an adaptive background model for robust processing in surrounding conditions. Object segmentation model detects pixels thresholded from local difference image between background and current image and extracts connected regions. Data association problem is solved by using feature extraction and object recognition model in searching window. We use Kalman filters for real-time tracking. The results of simulation show that the proposed method is good for tracking multiple moving objects in highway image sequences.