• Journal of Ocean Engineering and Technology
• /
• v.11 no.4
• /
• pp.189-196
• /
• 1997

An oil tracking system that monitors the spilt oil trajectory by using GPS was developed. The system consists of a tracking buoy deployed on the oil spilt area and an onshore(or onboard) monitoring station. The tracking buoy is equipped with GPS, signal converter, handy radio and battery while the monitoring station includes a station radio, signal converter, antennas and PC. The hull shape of buoy is designed to effectively simulate the spilt oil movement at sea surface. Radio sets for HAM are used as a data transmitter and a data receiving station, and signal converter is also for amateur use. A field experiment was conducted and it was shown that the integrated system is relable and robust. The developed oil tracking system reveals reatively good performance at reasonable cost. In favorable environment the system may communicate in the distance more than 50km.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2007.10a
• /
• pp.277-280
• /
• 2007

A moving object tracking algorithm for image searching based on specific color detection is proposed in this paper. That is preprocessed for a luminance variation and noise cancellation to be robust system. The motion tracking is used the difference between input image and reference image in R, G, B each channels for a moving image. The proposed method is enhanced to 15% fast in comparison with the contour tracking method and the matching method, and stable.

• Smart Media Journal
• /
• v.2 no.4
• /
• pp.9-19
• /
• 2013

This paper gives a review on three illumination issues of face tracking on smart phones: dark scenes, sudden lighting change and backlit effect. First, we propose a fast and robust face tracking method utilizing continuous adaptive mean shift algorithm (CAMSHIFT) and CbCr skin locus. Initially, the skin locus obtained from training video data. After that, a modified CAMSHIFT version based on the skin locus is accordingly provided. Second, we suggest an enhancement method to increase the chance of detecting faces, an important initialization step for face tracking, under dark illumination. The proposed method works comparably with traditional CAMSHIFT or particle filter, and outperforms these methods when dealing with our public video data with the three illumination issues mentioned above.

• Journal of the Korea Society of Computer and Information
• /
• v.22 no.7
• /
• pp.47-54
• /
• 2017

Recently, correlation filter based trackers have shown excellent tracking performance and computational efficiency. In order to enhance tracking performance in the correlation filter based tracker, search area which is image patch for finding target must include target. In this paper, two methods to discriminatively represent target in the search area are proposed. Firstly, search area location is estimated using pyramidal Lucas-Kanade algorithm. By estimating search area location before filtering, fast motion target can be included in the search area. Secondly, we investigate multi-channel Local Edge Pattern(LEP) which is insensitive to illumination and noise variation. Qualitative and quantitative experiments are performed with eight dataset, which includes ground truth. In comparison with method without search area estimation, our approach retain tracking for the fast motion target. Additionally, the proposed multi-channel LEP improves discriminative performance compare to existing features.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.14 no.3
• /
• pp.162-170
• /
• 2014

Appearance-based subspace models such as eigenfaces have been widely recognized as one of the most successful approaches to face recognition and tracking. The success of eigenfaces mainly has its origins in the benefits offered by principal component analysis (PCA), the representational power of the underlying generative process for high-dimensional noisy facial image data. The sparse extension of PCA (SPCA) has recently received significant attention in the research community. SPCA functions by imposing sparseness constraints on the eigenvectors, a technique that has been shown to yield more robust solutions in many applications. However, when SPCA is applied to facial images, the time and space complexity of PCA learning becomes a critical issue (e.g., real-time tracking). In this paper, we propose a very fast and scalable greedy forward selection algorithm for SPCA. Unlike a recent semidefinite program-relaxation method that suffers from complex optimization, our approach can process several thousands of data dimensions in reasonable time with little accuracy loss. The effectiveness of our proposed method was demonstrated on real-world face recognition and tracking datasets.

• Transactions of The Korea Fluid Power Systems Society
• /
• v.5 no.4
• /
• pp.26-31
• /
• 2008

This paper deals with the issue of position tracking control of a clamp-cylinder for injection moulding machine with electric-hydrostatic drives. A fixed displacement pump is utilized in combination with AC motor in order to directly control a clamp-cylinder. A clamp-cylinder may be required to operate under a variety of operating conditions. Therefore, robust control performance is important in position tracking control applications. In order to accommodate mismatches between the real plant and the model used for controller design, discrete-time sliding mode control is developed by combining a velocity feedforward loop. From tracking control experiments, it is shown that significant reduction in position tracking error is achieved through the use of sliding mode control.

• ETRI Journal
• /
• v.37 no.3
• /
• pp.551-561
• /
• 2015

We propose a novel multiple-object tracking algorithm for real-time intelligent video surveillance. We adopt particle filtering as our tracking framework. Background modeling and subtraction are used to generate a region of interest. A two-step pedestrian detection is employed to reduce the computation time of the algorithm, and an iterative particle repropagation method is proposed to enhance its tracking accuracy. A matching score for greedy data association is proposed to assign the detection results of the two-step pedestrian detector to trackers. Various experimental results demonstrate that the proposed algorithm tracks multiple objects accurately and precisely in real time.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.10a
• /
• pp.468-473
• /
• 1998

An intelligent multimode target tracking algorithm using fuzzy logic is presented. Multimode tracking represents a synergistic approach that utilizes a variety of tracking techniques(centroid, correlation, etc.) to overcome the limitations inherent in any single-mode tracker. The design challenge for this type of multimode tracker is the data fusion algorithm. designs for this algorithm are based on heuristic rather than analytical approaches. A correlation-tracking algorithm seeks to align the incoming target image with a reference in age of the target, but has a critical problem, so called drift phenomenon. In this paper we will suggest a robust correlation tracker with gradient preprocessor combined by centroid algorithm to overcome the drift problem.

• Proceedings of the KIEE Conference
• /
• 2001.07d
• /
• pp.2358-2361
• /
• 2001

In recent years there have been increasing interests in real-time object tracking with image information. Since image information is affected by illumination, this paper presents the real-time object tracking method based on neural networks which have robust characteristics under various illuminations. This paper proposes three steps to track the object and the fast tracking method. In the first step the object color is extracted using neural networks. In the second step we detect the object feature information based on invariant moment. Finally the object is tracked through a shape recognition using neural networks. To achieve the fast tracking performance, this paper first has a global search of entire image and tracks the object through local search when the object is recognized.

• Journal of Ocean Engineering and Technology
• /
• v.8 no.2
• /
• pp.56-63
• /
• 1994

This paper presents a design method of multivariable robust servo system for tracking control system for AUV(Autonomous Underwater Vehicle). In order to obtain the basic data for the design of the tracking control system, the control algorithm is evaluated in the view of computer simulation results. The tracking control is carried out for an AUV with 2 main thrusters, 2 side thrusters and 2 thrusters for the movement to up-down direction. The results of computer simulation show that the proposed multivariable servo system design method is an efficient method for the control performance of tracking control system of AUV under severe underwater environment.