• Journal of the Korea Society of Computer and Information
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• v.15 no.5
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• pp.23-31
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• 2010

With the advances in the information technology and mobile communications, we now face increasing demands for various services based on both of position tracking of moving objects and their efficient index scheme. Accordingly, the $TPR^*$-tree, which were proposed for efficiently tracking moving objects and predicting their positions in the future time, has drawn much intention. As the $TPR^*$-tree came from the R-tree that is suitable for indexing static objects, it does not support cheap update costs. Therefore, it seems to be very costly to index moving objects if there are frequent occurrences of node updates caused by continuously changing velocities and positions. If some moving objects with high velocities have node updates, in particular, then the $TPR^*$-tree may suffer from many unnecessary updates in the wide range of tree regions. To avoid such a problem, we propose a method that can keep fast-moving objects in the child nodes of the root node, thereby saving node update costs in the $TPR^*$-tree. To show our performance advantages and retaining $TPR^*$-tree features, we performed some performance experiments using a simulation technique.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.5
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• pp.1080-1088
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• 2004

In this paper, the interesting moving objects tracking algorithm using color information on Multi-Video camera against variance of intensity, shape and background is proposed. Moving objects are detected by using difference image method and integral projection method to background image and objects image only with hue area, after converting RGB color coordination of image which is input from multi-video camera into HSI color coordination. Hue information of the detected moving area are segmented to 24 levels from $0^{\circ}$ to $360^{\circ}$. It is used to the feature parameter of the moving objects that are three segmented hue levels with the highest distribution and difference among three segmented hue levels. To examine propriety of the proposed method, human images with variance of intensity and shape and human images with variance of intensity, shape and background are targeted for moving objects. As surveillance results of the interesting human, hue distribution level variation of the detected interesting human at each camera is under 2 level, and it is confirmed that the interesting human is tracked and surveilled by using feature parameters at cameras, automatically.

• Journal of KIISE:Software and Applications
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• v.29 no.5
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• pp.319-325
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• 2002

Tracking moving objects is one of the most important techniques in motion analysis and understanding, and it has many difficult problems to solve. Especially, estimating and identifying moving objects, when the background and moving objects vary dynamically, are very difficult. It is possible under such a complex environment that targets may disappear totally or partially due to occlusion by other objects. The Kalman filter has been used to estimate motion information and use the information in predicting the appearance of targets in succeeding frames. In this paper, we propose another version of the Kalman filter, to be called structured Kalman filter, which can successfully work its role of estimating motion information under a deteriorating condition such as occlusion. Experimental results show that the suggested approach is very effective in estimating and tracking non-rigid moving objects reliably.

• Journal of information and communication convergence engineering
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• v.6 no.1
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• pp.86-90
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• 2008

In this paper, I have presented a new approach which can track moving objects in unknown environments. This scheme is important in providing a computationally feasible alternative to complete enumeration of JPDA which is intractable. I have proved that given an artificial measurement and track's configuration, proposed scheme converges to a proper plot in a finite number of iterations. In this light, even if the performance is enhanced by using the relaxation, we also note that the difficulty in tuning the parameters of the relaxation scheme is critical aspect of this suggestion.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.433-437
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• 1988

Direct measurement of the relative position between the end effector of robot and moving objects reduces difficulties caused by the joint encoder reading and transformation. For those purpose, the on-line sensing method using PSD sensor was developed in this paper. The sensor was calibrated on the precision table. Then, the relative position of a moving objects on the conveyor was measured while the robot was tracking the one.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.1
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• pp.142-151
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• 2015

This paper proposes a method for detection of objects temporally stop moving in video sequences taken by a moving camera. Even though the consequence of missed detection of those objects could be catastrophic in terms of application level requirements, not much attention has been paid in conventional approaches. In the proposed method, we introduce cues for consistent detection and tracking of objects: motion potential, position potential, and color distribution similarity. Integration of the three cues in the graph-cut algorithm makes possible to detect objects that temporally stop moving and are newly appearing. Experiment results prove that the proposed method can not only detect moving objects but also track objects stop moving.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1992-1995
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• 2003

An adaptive active contour algorithm which shows stable object tracking performance under the moving or deformable environments, is proposed. In order to cope with local deformation of the object, an energy map is generated from the difference of the consecutive images and a new energy function based on the energy map is presented. The algorithm is evaluated on a set of artificial and real images to verify the efficiencies and test results show the stable tracking performance for the moving objects.

• Journal of Electrical Engineering and Technology
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• v.9 no.6
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• pp.2126-2133
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• 2014

We present a scalable object tracking framework, which is capable of removing shadows and tracking the people. The framework consists of background subtraction, fuzzy based shadow removal and boundary tracking algorithm. This work proposes a general-purpose method that combines statistical assumptions with the object-level knowledge of moving objects, apparent objects, and shadows acquired in the processing of the previous frames. Pixels belonging to moving objects and shadows are processed differently in order to supply an object-based selective update. Experimental results demonstrate that the proposed method is able to track the object boundaries under significant shadows with noise and background clutter.

• The Journal of the Korea Contents Association
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• v.3 no.1
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• pp.58-63
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• 2003

In this paper, an object tracking system in a known environment is proposed. It extracts moving area shaped on objects in video sequences and decides tracks of moving objects. Color invarianoe features are exploited to extract the plausible object blocks and the degree of radial homogeneity, which is utilized as local block feature to find out the block correspondences. The experimental results are given.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.894-897
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• 2012

We propose a effective method using the HOG (Histogram of Oriented Gradients) feature vector to track individual objects in an environment which multiple objects are moving. The proposed algorithm consists of pre-processing, object detection and object tracking. We experimented with six videos which have various trajectories and the movement. When occlusion between objects was occurred, we identified individual object by using center and predicted coordinates of moving objects. The algorithm shows 85.45% of tracking rate in the videos we experimented. We expect the proposed system is utilized in security systems which require the alalysis of the position and motion pattern of objects.