• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.4
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• pp.708-717
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• 2017

Tracking of sound-location is widely used in various area such as intelligent CCTV, video conference and voice commander. In this paper we introduce the real-time sound-location tracking method for smart lecture system using TDoA(Time Difference of Arrival) with orthogonal microphone array on the ceiling. Through discussion on some models of TDoA detection, cross correlation method using linear microphone array is proposed. Orthogonal array with 5 microphone could detect omni direction of sound-location. For real-time detection we adopt the threshold of received energy for eliminating no-voice interval, signed cross correlation for reducing computational complexity. The detected azimuth angles are processed using median filter for lowering the angle deviation. The proposed system is implemented with high performance MCU of TMS320F379D and MEMs microphone module and shows the accuracy of 0.5 and 6.5 in degree for white noise and lectured voice, respectively.

• Journal of the Semiconductor & Display Technology
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• v.10 no.3
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• pp.21-28
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• 2011

In recent years, owing to the development of the image processing technology, the research to build control system using a vision sensor is stimulated. However, a random time delay must be considered, because it works of a various time to get a result of an image processing in the system. It can be seen as an obstacle factor to a control of visual tracking in real system. In this paper, implementing two vision controllers each, first one is made up PID controller and the second one is consisted of a Smith Predictor, the possibility was shown to overcome a problem of a random time delay in a visual tracking system. A number of simulations and experiments were done to show the validity of this study.

• Speech Sciences
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• v.3
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• pp.119-131
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• 1998

We have developed a keyword spotting system for automatic speech editing. This system recognizes the only keyword 'MBC news' and then sends the time information to the host system. We adopted a vocabulary dependent model based on continuous hidden Markov model, and the Viterbi search was used for recognizing the keyword. In recognizing the keyword, the system uses a parallel network where HMM models are connected independently and back-tracking information for reducing false alarms and missing. We especially focused on implementing a stable and practical real-time system.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2258-2263
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• 2003

This paper presents the design and development of an optimal fuzzy logic controller (FLC) for a laser tracking system. An optimal intelligent fuzzy logic controller was founded on integral criterion of the fuzzy models and three-dimensional fuzzy control. Research had been also concentrated on the methods for multivariable fuzzy models for the purposes of real-time process. Simulation results have shown remarkable tracking performance of this fuzzy PID controller.

• IE interfaces
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• v.25 no.1
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• pp.114-126
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• 2012

This study describes a real-time location monitoring system developed for efficient operation of workplace in plant equipment maker. This monitoring system can be applied for indoor and outdoor working environment respectively. By using the real-time tracking system based on RTLS, it is possible to track worker's movement and location of working object under indoor working environment. For outdoor working environment, the real-time monitoring system based on IDGPS is applied for work safety and balanced workload. A case study is provided to evaluate the performance of the real-time monitoring system.

• Journal of the Semiconductor & Display Technology
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• v.16 no.4
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• pp.97-102
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• 2017

Object detection and tracking have become one of the most active research areas in the past few years, and play an important role in computer vision applications over our daily life. Many tracking techniques are proposed, and Camshift is an effective algorithm for real time dynamic object tracking, which uses only color features, so that the algorithm is sensitive to illumination and some other environmental elements. This paper presents and implements an effective moving object detection and tracking to reduce the influence of illumination interference, which improve the performance of tracking under similar color background. The implemented prototype system recognizes object using invariant features, and reduces the dimension of feature descriptor to rectify the problems. The experimental result shows that that the system is superior to the existing methods in processing time, and maintains better problem ratios in various environments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.1
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• pp.197-205
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• 2006

This paper presents the moving object tracking method using vision system. In order to track object in real time, the image of moving object have to be located the origin of the image coordinate axes. Accordingly, Fuzzy Control System is investigated for tracking the moving object, which control the camera module with Pan/Tilt mechanism. Hereafter, so the this system is applied to mobile robot, we design and implement image processing board for vision system. Also fuzzy controller is implemented to the StrongArm board. Finally, the proposed fuzzy controller is useful for the real-time moving object tracking system by experiment.

• 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.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.365-368
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• 2001

This work describes a real-time method, based on motion energy detection, for detecting and tracking moving object in the consecutive image sequences. The motion of moving objects is detected by taking the difference of the two consecutive image frames. In addition an edge information of the current image is utilized in order to further increase the accuracy of detection. We can track the moving objects continuously by detecting the motion of objects from the sequence of image frames. A prototype system has been implemented using a TI TMS320C6201 EVM fixed-point DSP board, which can successfully track a moving human in real-time.

• Journal of Advanced Navigation Technology
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• v.14 no.6
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• pp.783-790
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• 2010

For safety navigation of ships at sea, ships monitor their location obtained from Global Positioning Satellite System (GNSS). In this study, we computed near-real-time positions of a ship at sea using GPS Precise Point Positioning (PPP) technique and analyzed precision of the near-real-time positions. We conducted ship borne GPS observations in the south sea of Korea. To process the GPS data using PPP technique, GIPSY-OASIS (GPS Inferred Positioning System-Orbit Analysis and Simulation Software) developed by the Jet Propulsion Laboratory was used. Antenna phase center variations, ocean tidal loading displacements, and azimuthal gradients of the atmosphere were corrected or estimated as standard procedures of high-precision GIPSY-OASIS data processing. As a result, the precisions of near-real-time positions was ~1cm.