• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.6
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• pp.194-203
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• 2008

Though conventional video surveillance systems such as CCTV depended on operators, recently developed intelligent surveillance systems no longer needed operators. However, these new intelligent surveillance systems have their own problems such as Occlusion, changing scale of target object, and affine. This paper handled information damage caused by changing the scale of the target object among other objects. Due to the change of the scale, the inaccurate information of target can be obtained when we update the background information. To handle this problem, we introduce a solution for information damage caused by problem of changing scale of target object located among other objects. Specifically, we suggest multi-stage sampling particle filter based advanced MSER for object tracking system. Through this method, the problem caused by changing scale of target can be avoided.

• International Journal of Aeronautical and Space Sciences
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• v.3 no.1
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• pp.39-49
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• 2002

This paper presents a robust tracker design method that is specific to the trajectories of target aircraft. This method assumes that representative trajectories of the target aircraft are available. The exact trajectories known to the tracker enables the incorporation of the exact data in the tracker design instead of the measurement data. An estimator is designed to have acceptable performance in tracking a finite number of different target trajectories with a capability to trade off the mean and maximum errors between the exact trajectories and the estimated or predicted trajectories. Constant estimator gains that minimize the cost functions related to the estimation or prediction error are computed off-line from an iterative algorithm. This tracker design method is applied to the longitudinal motion tracking of target aircraft.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.5
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• pp.94-104
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• 2000

The accuracy and reliability of the target tracking is very critical issue in the design of automotive collision warning radar A significant problem in multi-target tracking (MTT) is the target-to-measurement data association If an incorrect measurement is associated with a target, the target could diverge the track and be prematurely terminated or cause other targets to also diverge the track. Most methods for target-to-measurement data association tend to coalesce neighboring targets Therefore, many algorithms have been developed to solve this data association problem. In this paper, a new multi-target data association method based on order statistics is described The new approaches. called the order statistics probabilistic data association (OSPDA) and the order statistics joint probabilistic data association (OSJPDA), are formulated using the association probabilities of the probabilistic data association (PDA) and the joint probabilistic data association (JPDA) filters, respectively Using the decision logic. an optimal or near optimal target-to-measurement data association is made A computer simulation of the proposed method in a heavy cluttered condition is given, including a comparison With the nearest-neighbor CNN). the PDA, and the JPDA filters, Simulation results show that the performances of the OSPDA filter and the OSJPDA filter are superior to those of the PDA filter and the JPDA filter in terms of tracking accuracy about 18% and 19%, respectively In addition, the proposed method is implemented using a developed digital signal processing (DSP) board which can be interfaced with the engine control unit (ECU) of car engine and with the d?xer through the controller area network (CAN)

• The Journal of the Acoustical Society of Korea
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• v.24 no.5
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• pp.294-300
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• 2005

Generally, traditional approaches to track the target position are to estimate ranges and bearings by 2-D MUSIC (MUltiple 519na1 Classification) method. and to associate estimates of 2-D MUSIC made at different time points with the right targets by JPDA (Joint Probabilistic Data Association) filter in the near field. However, the disadvantages of these approaches are that these have the data association Problem in tracking multiple targets. and that these require the heavy computational load in estimating a 2-D range/bearing spectrum. In case multiple targets are adjacent. the tracking performance degrades seriously because the estimate of each target's Position has a large error. In this paper, we proposed a new tracking algorithm using Position innovations extracted from the senor output covariance matrix in the near field. The proposed algorithm is demonstrated by the computer simulations dealing with the tracking of multiple closing and crossing targets.

• Journal of Korea Multimedia Society
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• v.22 no.3
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• pp.357-365
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• 2019

In this paper, we suggest the tracking method of moving multi-objects in maritime environments. The image acquisition is conducted using IR(InfraRed) camera sensors on an airborne platform. Under the circumstance of maritime, the qualities of IR images can be significantly degraded due to the clutter influence, which directly gives rise to a tracking loss problem. In order to reduce the effects from the clutters, we introduce a technical approach under Man-In-The-Loop(MITL) system for enhancing the tracking performance. To demonstrate the robustness of the proposed approach based on VTG(Valid Tracking Gate), the simulations are conducted utilizing the airborne IR video sequences: Then, the tracking performances are compared with the existing Kalman Filter tracking techniques.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.828-831
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• 1997

One of the most important design factor for the image tracker is the speed of the data processing which allows real-time operation of the system and provides reasonably accurate performance at the same time. Use of powerful DSP alone does not guarantee to meet such requirement. In this paper, a simple efficient algorithm for real-time multi-target image tracking is suggested. The suggested method is based on a recursive centroiding technique and color table look-up. This method has been successfully implemented in a image processing system for Micro-Robot Soccer Tournament(MIROSOT). This tracker can track positions of a ball, 3 enemies, and 3 agents at the same time. The experimental results show that the processing time for each frame of image is less than 7ms, which is well within the 60Hz sampling interval for real-time operation.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.789-790
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• 2008

In this paper, we introduce the multi-target-based auto surveillance algorithm. Multi-target-based surveillance system detects intrusion objects in the specified areas. The proposed algorithm can divide into two parts: i) background generation, ii) object extraction. In this paper, one of the optical flow equation methods for estimation of gradient method used to generate the background [2]. In addition, the objects and back- ground video images that are continually entering the differential extraction.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.18 no.1
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• pp.39-44
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• 2010

A method is presented of dynamic determination of mode transition probability for IMM in order to improve the accuracy performance of maneuvering target tracking for air traffic control surveillance processing system under multiple radar environment. It is shown that dynamic determination of mode transition probability based on the time intervals between the data input from multiple radars gives the optimized performance in terms of position estimation accuracy.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.3
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• pp.187-192
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• 2015

Detecting human in images is a challenging task owing to their variable appearance and the wide range of poses the they can adopt. The first need is a robust feature set that allows the human form to be discriminated cleanly, even in cluttered background under difficult illumination. A large number of vision application rely on matching keypoints across images. These days, the deployment of vision algorithms on smart phones and embedded device with low memory and computation complexity has even upped the ante: the goal is to make descriptors faster compute, more compact while remaining robust scale, rotation and noise. In this paper we focus on improving the speed of pedestrian(walking person) detection using Histogram of Oriented Gradient(HOG) descriptors provide excellent performance and tracking using kalman filter.

• Journal of the Semiconductor & Display Technology
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• v.17 no.2
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• pp.67-70
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• 2018

Object detection and tracking is an exciting and interesting research area in the field of computer vision, and its technologies have been widely used in various application systems such as surveillance, military, and augmented reality. This paper proposes and implements a novel and more robust object recognition and tracking system to localize and track multiple objects from input images, which estimates target state using the likelihoods obtained from multiple CNNs. As the experimental result, the proposed algorithm is effective to handle multi-modal target appearances and other exceptions.