• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.9
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• pp.1632-1652
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• 2011

This paper considers the object tracking problem in three dimensional (3-D) space when the azimuth and elevation of the object are available from the passive acoustic sensor. The particle filtering technique can be directly applied to estimate the 3-D object location, but we propose to decompose the 3-D particle filter into the three planes' particle filters, which are individually designed for the 2-D bearings-only tracking problems. 2-D bearing information is derived from the azimuth and elevation of the object to be used for the 2-D particle filter. Two estimates of three planes' particle filters are selected based on the characterization of the acoustic sensor operation in a noisy environment. The Cramer-Rao Lower Bound of the proposed 2-D particle filter-based algorithm is derived and compared against the algorithm that is based on the direct 3-D particle filter.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.586-591
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• 2009

In this paper, we propose the mobile object tracking algorithm based on the feature vector using particle filter. To do this, first, we detect the movement area of mobile object by using RGB color model and extract the feature vectors of the input image by using the KLT-algorithm. And then, we get the first feature vectors by matching extracted feature vectors to the detected movement area. Second, we detect new movement area of the mobile objects by using RGB and HSI color model, and get the new feature vectors by applying the new feature vectors to the snake algorithm. And then, we find the second feature vectors by applying the second feature vectors to new movement area. So, we design the mobile object tracking algorithm by applying the second feature vectors to particle filter. Finally, we validate the applicability of the proposed method through the experience in a complex environment.

• International Journal of Control, Automation, and Systems
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• v.1 no.4
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• pp.495-502
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• 2003

This paper focuses on the implementation of an efficient tracking method of a moving object using optimal representative blocks by way of a pan-tilt camera. The key idea is derived from the fact that when the image size of a moving object is shrunk in an image frame according to the distance between the mobile robot camera and the object in motion, the tracking performance of a moving object can be improved by reducing the size of representative blocks according to the object image size. Motion estimations using Edge Detection (ED) and Block-Matching Algorithm (BMA) are regularly employed to track objects by vision sensors. However, these methods often neglect the real-time vision data since these schemes suffer from heavy computational load. In this paper, a representative block able to significantly reduce the amount of data to be computed, is defined and optimized by changing the size of representative blocks according to the size of the object in the image frame in order to improve tracking performance. The proposed algorithm is verified experimentally by using a two degree-of- freedom active camera mounted on a mobile robot.

• 한국정보디스플레이학회:학술대회논문집
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• 2000.01a
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• pp.79-80
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• 2000

General stereo vision system shows things in 3D, using two visions of left and right side. When the viewpoints of left/right sides are not in accord with each other, it gives fatigue to human eyes and prevents them from having the 3-D feeling. Also, it would be difficult to track mobile objects that are not in the middle of a screen. Therefore, the object tracking function of stereo vision system is to control tracking objects to always be in the middle of a screen while controlling convergence angles of mobile objects in the input image of the left/right cameras. In this paper, object-tracker in stereo vision system is presented which would track mobile objects by using block matching algorithm of preprocessing and JTC.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.113-117
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• 2005

This paper describes a visual control scheme, fuzzy logic system for visual servoing of an autonomous mobile robot. An existing communication autonomous mobile robot always needs to keep the object in image to detect the moving object. This is a problem in an autonomous mobile robot for spontaneous activity. To solve it, some features for an object are taken from an image and then use in the design of fuzzy logic system for decision of moving location and direction of visual servoing contrivance(apparatus). So continuous tracking is possible by moving the visual servoing contrivance. We present some simulation results and further studies in the Section of Simulation and Concluding Remarks.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.165-171
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• 2004

Robots will be able to coexist with humans and support humans effectively in near future. One of the most important aspects in the development of human-friendly robots is to cooperation between humans and robots. In this paper, we proposed a method for multi-object identification in order to achieve such human-centered system and robot localization in intelligent space. The intelligent space is the space where many intelligent devices, such as computers and sensors, are distributed. The Intelligent Space achieves the human centered services by accelerating the physical and psychological interaction between humans and intelligent devices. As an intelligent device of the Intelligent Space, a color CCD camera module, which includes processing and networking part, has been chosen. The Intelligent Space requires functions of identifying and tracking the multiple objects to realize appropriate services to users under the multi-camera environments. In order to achieve seamless tracking and location estimation many camera modules are distributed. They causes some errors about object identification among different camera modules. This paper describes appearance based object representation for the distributed vision system in Intelligent Space to achieve consistent labeling of all objects. Then, we discuss how to learn the object color appearance model and how to achieve the multi-object tracking under occlusions.

• Journal of the Korea Society of Computer and Information
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• v.21 no.6
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• pp.63-69
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• 2016

In this paper, we proposed the location tracking system based on MS-Based/Assisted(Mobile Station-Based and Assisted) location trigger service model with context-awareness for the intelligent location tracking of moving objects. It provides the proper resulting value that matches the context of users through the analysis about the situation of the user, physical environment, computing resource and the existing information on user input. In order to provide real-time data, we proposed the location tracking system which realizes the intelligent information such as the expecting arrival time and passing the specific area of the moving object by adopting the location trigger. So, it derives to minimize the costs of communication for the mobile object tracking applications. The proposed location tracking system based on context-awareness can be used for realtime monitoring, intelligent alarm/action, setting up of the optimized moving path, dynamic adjustment of strategies and policies. So it has the advantage to develop the application system which is aimed at optimization of the object tracking and movement.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.7
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• pp.599-604
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• 2013

Path planning of mobile robots has a purpose to design an optimal path from an initial position to a target point. Minimum driving time, minimum driving distance and minimum driving error might be considered in choosing the optimal path and are correlated to each other. In this paper, an efficient driving trajectory is planned in a real situation where a mobile robot follows a moving object. Position and distance of the moving object are obtained using a web camera, and the rotation angular and linear velocities are estimated using Kalman filters to predict the trajectory of the moving object. Finally, the mobile robot follows the moving object using a single curvature trajectory by estimating the trajectory of the moving object. Using the estimation by Kalman filters and the single curvature in the trajectory planning, the total tracking distance and time saved amounts to about 7%. The effectiveness of the proposed algorithm has been verified through real tracking experiments.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1410-1429
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• 2017

Mobility arises naturally in the Internet of Things networks, since the location of mobile objects, e.g., mobile agents, mobile software, mobile things, or users with wireless hardware, changes as they move. Tracking their current location is essential to mobile computing. To overcome the scalability problem, hierarchical architectures of location databases have been proposed. When location updates and lookups for mobile objects are localized, these architectures become effective. However, the network signaling costs and the execution number of database operations increase particularly when the scale of the architectures and the numbers of databases becomes large to accommodate a great number of objects. This disadvantage can be alleviated by a location caching scheme which exploits the spatial and temporal locality in location lookup. In this paper, we propose a hierarchical location caching scheme, which acclimates the existing location caching scheme to a hierarchical architecture of location databases. The performance analysis indicates that the adjustment of such thresholds has an impact on cost reduction in the proposed scheme.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1917-1920
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• 2003

Automatic tracking of a moving object such as a person is a demanding technique especially in surveillance. This paper describes an experimental system for tracking a moving object on the ground by using a visually controlled aerial robot. A blimp is used as the aerial robot in the proposed system because of its locality in motion and its silent nature. The developed blimp is equipped with a camera for taking downward images and four rotors for controlling the progression. Once a camera takes an image of a specified moving object on the ground, the blimp is controlled so that it follows the object by the employment of the visual information. Experimental results show satisfactory performance of the system. Advantages of the present system include that images from the air often enable us to avoid occlusion among objects on the ground and that blimp’s progression is much less restricted in the air than, e.g., a mobile robot running on the ground.