• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.6
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• pp.141-152
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• 2011

Growing efforts and interests of security techniques in a diverse surveillance environment, the intelligent surveillance system, which is capable of automatically detecting and tracking target objects in multi-cameras environment, is actively developing in a security community. In this paper, we propose an effective visual surveillance system that is avaliable to track objects continuously in multiple non-overlapped cameras. The proposed object tracking scheme consists of object tracking module and tracking management module, which are based on hand-off scheme and protocol. The object tracking module, runs on IP camera, provides object tracking information generation, object tracking information distribution and similarity comparison function. On the other hand, the tracking management module, runs on video control server, provides realtime object tracking reception, object tracking information retrieval and IP camera control functions. The proposed object tracking scheme allows comprehensive framework that can be used in a diverse range of application, because it doesn't rely on the particular surveillance system or object tracking techniques.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.6
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• pp.897-906
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• 2017

Projection Mapping, also known as Spatial Augmented Reality(SAR) has attracted much attention recently and used for many division, which can augment physical objects with projected various virtual replications. However, conventional approaches towards projection mapping have faced some limitations. Target objects' geometric transformation property does not considered, and movements of flexible objects-like paper are hard to handle, such as folding and bending as natural interaction. Also, precise registration and tracking has been a cumbersome process in the past. While there have been many researches on Projection Mapping on static objects, dynamic projection mapping that can keep tracking of a moving flexible target and aligning the projection at interactive level is still a challenge. Therefore, this paper propose a new method using Unity3D and ARToolkit for high-speed robust tracking and dynamic projection mapping onto non-rigid deforming objects rapidly and interactively. The method consists of four stages, forming cubic bezier surface, process of rendering transformation values, multiple marker recognition and tracking, and webcam real time-lapse imaging. Users can fold, curve, bend and twist to make interaction. This method can achieve three high-quality results. First, the system can detect the strong deformation of objects. Second, it reduces the occlusion error which reduces the misalignment between the target object and the projected video. Lastly, the accuracy and the robustness of this method can make result values to be projected exactly onto the target object in real-time with high-speed and precise transformation tracking.

• Journal of Advanced Navigation Technology
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• v.15 no.6
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• pp.1132-1137
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• 2011

In this paper, we propose Modified Multi CAMShift Algorithm(Modified Multi Continuously Adaptive Mean Shift Algorithm) that extracts skin color area and tracks several human body parts for real-time human tracking system. Skin color area is extracted by filtering input image in predefined RGB value range. These areas are initial search windows of hands and face for tracking. Gaussian background model prevents search window expending because it restricts skin color area. Also when occluding between these areas, we give more weights in occlusion area and move mass center of target area in color probability distribution image. As result, the proposed algorithm performs better than the original CAMShift approach in multiple object tracking and even when occluding of objects with similar colors.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7C
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• pp.527-537
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• 2012

In this paper, we propose unmanned vehicle based tracking network (UVTN) architecture and algorithms which employ multiple autonomous unmanned ground vehicles (AUGV) to efficiently follow targets in a group. The goal of UVTN is to maximize the service coverage while tracking target nodes for monitoring or providing the network access. In order to achieve this goal, UVTN performs periodic expansion and contraction which results in optimized redistribution of AUGV's in the network. Also, enhanced algorithms such as fast contraction and longest first are also discussed to improve the performance of UVTN in terms of the average coverage ratio and traveled distance. Simulation results show that the proposed UVTN and enhanced algorithms can effectively track the moving target and provide the consistent coverage.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.38 no.6
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• pp.1-8
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• 2001

Recently, Ryu et al. proposed a multiple target angle tracking algorithm using the angular innovation extracted from the estimated signal subspace. This algorithm obtains the angles of targets and associates data simultaneously. Therefore, it has a simple structure without data association problem. However it requires the calculation of the inverse of a real matrix with dimension (2N+1)${\times}$(2N+1) to obtain the angular innovations of N targets. In this paper, a new linear equation for angular innovation is proposed using the fact that the projection error is zero when the target steering vector is projected onto the signal subspace. As a result, the proposed algorithm dose not require the matrix inversion and is computationally efficient.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.12
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• pp.689-697
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• 2005

In this paper, an application of a decentralized $H_{\infty}$ controller(DHC) to multiple controlled-permanent magnet(CMAG) magnetic levitation(Maglev) systems is presented. The designed DHC using two Riccati equations iteratively has simpler structure and needs less computational loads than conventional centralized $H_{\infty}$ controller. A target plant is a hybrid-type CMAG system with permanent magnet and coil, and its mathematical model is firstly derived to design the DHC. To implement the designed algorithm, a real Maglev vehicle system including digital controller, chopper, sensor, etc., is manufactured. To compare the performances of the DHC method with an observer-based state feedback control(OSFC), the input tracking and disturbance rejection characteristics are experimentally tested. As performance indices(PI), integral of squared error(ISE), integral of absolute error(IAE), integral of time multiplied by absolute error(ITAE) and integral of time multiplied by squared error(ITSE) are used. From the experimental results, it can be seen that the input tracking and disturbance rejection performances of the DHC are better than those of the conventional controller.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.25 no.5
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• pp.354-361
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• 2016

Parallel robots are usually used for performing pick-and-place motion to increase productivity in high-speed environments. The present study proposes a high-speed parallel robot and a control approach to improve the tracking performance for the purpose of handling a solar cell. However, the target processes are not limited to the solar cell-handling field. Therefore, a delta-type parallel manipulator is designed, and a ball joint structure is specifically proposed to increase the allowed angle that would meet the required workspace. A control algorithm considering the synchronization between multiple joints in a closed-chain mechanism is also suggested to improve the tracking performance, where the tracking and synchronization errors are simultaneously considered. In addition, a prototype machine with the proposed ball joint is implemented. A satisfactory tracking performance is achieved by applying the proposed control algorithm, with a cycle time of 0.3 s for a 0.1 kg payload.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.1
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• pp.96-107
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• 2014

Tracking the tactical object is a fundamental affair in network-equipped modern warfare. Geodetic coordinate system based on longitude, latitude, and height is suitable to represent the location of tactical objects considering multi platform data fusion. The motion of tactical object described as a dynamic model requires an appropriate filtering to overcome the system and measurement noise in acquiring information from multiple sensors. This paper introduces the filter suitable for multi-sensor data fusion and tactical object tracking, particularly the unscented transform(UT) and its detail. The UT in Unscented Kalman Filter(UKF) uses a few samples to estimate nonlinear-propagated statistic parameters, and UT has better performance and complexity than the conventional linearization method. We show the effects of UT-based filtering via simulation considering practical tactical object tracking scenario.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.1
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• pp.136-142
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• 2007

This paper proposes a new approach on nonlinear maneuvering target tracking. In this paper, proposed algorithm is the Kalman filter based on the adaptive interactive multiple model using the concept of predicted impact point and utilize modified Kalman filter regarding the error between measurement position and predicted impact point. The unknown target acceleration is regarded as an additional process noise to the target model, and each sub-model is characterized in accordance with the valiance of the overall process noise which is obtained on the basis of each acceleration interval. To compensate the decreasing performance of Kalman filter in nonlinear maneuver, we construct optional algorithm to utilize proposed method or Kalman filter selectively. To effectively estimate the acceleration during the target maneuvering, the rapid increase of the noise scale is recognized as the acceleration to be used in maneuvering target's movement equation. And a few examples are presented to show suggested algorithm's executional potential.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.6
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• pp.15-29
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• 2018

This paper proposes an enhanced object tracking algorithm to compensate the lack of temporal information in existing particle swarm optimization based object trackers using the trajectory of the target object. The proposed scheme also enables the tracking and documentation of the location of an online updated set of distractions. Based on the trajectories information and the distraction set, a rule based approach with adaptive parameters is utilized for occlusion detection and determination of the target position. Compare to existing algorithms, the proposed approach provides more comprehensive use of available information and does not require manual adjustment of threshold values. Moreover, an effective weight adjustment function is proposed to alleviate the diversity loss and pre-mature convergence problem in particle swarm optimization. The proposed weight function ensures particles to search thoroughly in the frame before convergence to an optimum solution. In the existence of multiple objects with similar feature composition, this algorithm is tested to significantly reduce convergence to nearby distractions compared to the other existing swarm intelligence based object trackers.