• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.5
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• pp.637-642
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• 2011

In this paper, a new technique to estimate the distances between a vanishing point and moving objects is proposed. A vanishing point for an input image is estimated and it use to extract distance form the vanishing point to a moving object. Using the obtained distances, moving objects is extracted. In simulation results, several performances for a test image sequnce is shown.

• Journal of Korea Spatial Information System Society
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• v.8 no.2 s.17
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• pp.53-73
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• 2006

Recently, the need for Location-Based Services (LBS) has increased due to the development of mobile devices, such as PDAs, cellular phones and GPS. As a moving object database that stores and manages the positions of moving objects is the core technology of LBS, the scheme for maintaining the main memory DBMS to the server is necessary to store and process frequent reported positions of moving objects efficiently. However, previous works on a moving object database have studied mostly a disk based moving object index that is not guaranteed to work efficiently in the main memory DBMS because these indexes did not consider characteristics of the main memory. It is necessary to study the main memory index scheme for a moving object database. In this paper, we propose the main memory index scheme based on the R-tree for storing and processing positions of moving objects efficiently in the main memory DBMS. The proposed index scheme, which uses a growing node structure, prevents the splitting cost from increasing by delaying the node splitting when a node overflows. The proposed scheme also improves the search performance by using a MergeAndSplit policy for reducing overlaps between nodes and a LargeDomainNodeSplit policy for reducing a ratio of a domain size occupied by node's MBRs. Our experiments show that the proposed index scheme outperforms the existing index scheme on the maximum 30% for range queries.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.712-715
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• 1997

In image jacobian based visual servoing, generally, inverse jacobian should be calculated by complicated coordinate transformations. These are required excessive computation and the singularity of the image jacobian should be considered. This paper presents a visual servoing to control the pose of the robotic manipulator for tracking and grasping 3-D moving object whose pose and motion parameters are unknown. Because the object is in motion tracking and grasping must be done on-line and the controller must have continuous learning ability. In order to estimate parameters of a moving object we use the kalman filter. And for tracking and grasping a moving object we use a fuzzy inference based reinforcement learning algorithm of dynamic recurrent neural networks. Computer simulation results are presented to demonstrate the performance of this visual servoing

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.2033-2036
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• 2004

A novel approach to estimate the real time moving trajectory of an object is proposed in this paper. The object position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Kalman filter and neural networks are utilized. Since the Kalman filter needs to approximate a non-linear system into a linear model to estimate the states, there always exist errors as well as uncertainties again. To resolve this problem, the neural networks are adopted in this approach, which have high adaptability with the memory of the input-output relationship. Kohonen Network(Self-Organized Map) is selected to learn the motion trajectory since it is spatially oriented. The superiority of the proposed algorithm is demonstrated through the real experiments.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.302-305
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• 1996

This paper presents a visual servoing combined by Neural Network with optimal structure and predictive control for robotic manipulators to tracking or grasping of the moving object. Using the four feature image information from CCD camera attached to end-effector of RV-M2 robot manipulator having 5 dof, we want to predict the updated position of the object. The Kalman filter is used to estimate the motion parameters, namely the state vector of the moving object in successive image frames, and using the multi layer feedforward neural network that permits the connection of other layers, evolutionary programming(EP) that search the structure and weight of the neural network, and evolution strategies(ES) which training the weight of neuron, we optimized the net structure of control scheme. The validity and effectiveness of the proposed control scheme and predictive control of moving object will be verified by computer simulation.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.832-834
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• 1999

This paper is a study on the real-position measurements of mobile object using n network. 2-D PSD sensor is used to measure th position of moving object with light source. Position Sensitive Detector(PSD) is an useful which can be used to measure the position o incidence light in accuracy and in real-time. T the position of light source of moving target, neural network technique are proposed and applied. Real-time position measurements of the mobile robot with light source is examined to validate the proposed method. It is shown that the proposed technique provides accurate position estimation of the moving object.

• Journal of Korea Multimedia Society
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• v.12 no.12
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• pp.1745-1754
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• 2009

PTZ (Pan-Tilt-Zoom) camera based surveillance systems are enlarging their field of application due to their wide observable area. We aimed to detect both static and moving objects in automated working space by using a PTZ camera. For object detection we used background difference method because of the high quality segmentation. However, the method has a problem called 'hole' that is caused by non-continuous surveillance of the PTZ camera and its own characteristics. Moreover, the occlusion which occurs when the moving object overlaps with the static object should be solved for robust object detection. In this paper, we suggest a region-based technique for updating background images thereby overcoming the hole and occlusion problem. Through experiments with real scenes, it was verified that meaningful static and/or moving objects were detected very well.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.77.5-77
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• 2001

A Robot vision system with a visual skill so as take information for arbitrary target or object has been applied to auto-inspection and assembling system. It catches the moving target with the manipulator by using the information from the vision system. The robot needs some information where the moving object will place after certain time. A camera is fixed on a robot manipulator, not on the fixed support outside of the robot. It secures wider working area than the fixed camera, and it dedicates to auto scanning of the object. It computes some information on the object center, angle and speed by vision data, and can guess grabbing spot by arriving time. When the location ...

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.677-680
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• 2004

In the mobile environment, according to the movement of the object, the query finds the nearest special object or place from object position. However, because query object moves continuously in the mobile environment, query demand changes according to the direction attribute of query object. Also, in the case of moving of query object and simply the minimum distance value of query result, sometimes we find the result against the query object direction. Especially, in most road condition, as user has to return after reaching U-turn area, user rather spends time and cost. Therefore, in order to solve those problems, in this paper we propose the nearest neighbor method considering moving object position and direction for mobile recommendation system.