• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.6
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• pp.323-330
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• 2021

Visual object tracking is a challenging area of study in the field of computer vision due to many difficult problems, including a fast variation of target shape, occlusion, and arbitrary ground truth object designation. In this paper, we focus on the reinforced feature of the dynamic search area to get better performance than conventional discriminative model prediction trackers on the condition when the accuracy deteriorates since low feature discrimination. We propose a reinforced input feature method shown like the spotlight effect on the dynamic search area of the target tracking. This method can be used to improve performances for deep learning based discriminative model prediction tracker, also various types of trackers which are used to infer the center of the target based on the visual object tracking. The proposed method shows the improved tracking performance than the baseline trackers, achieving a relative gain of 38% quantitative improvement from 0.433 to 0.601 F-score at the visual object tracking evaluation.

• ETRI Journal
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• v.38 no.5
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• pp.1019-1029
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• 2016

The probability hypothesis density (PHD) filter is an effective means to track multiple targets in that it avoids explicit data associations between the measurements and targets. However, the target birth intensity as a prior is assumed to be known before tracking in a traditional target-tracking algorithm; otherwise, the performance of a conventional PHD filter will decline sharply. Aiming at this problem, a novel target birth intensity scheme and an improved measurement-driven scheme are incorporated into the PHD filter. The target birth intensity estimation scheme, composed of both PHD pre-filter technology and a target velocity extent method, is introduced to recursively estimate the target birth intensity by using the latest measurements at each time step. Second, based on the improved measurement-driven scheme, the measurement set at each time step is divided into the survival target measurement set, birth target measurement set, and clutter set, and meanwhile, the survival and birth target measurement sets are used to update the survival and birth targets, respectively. Lastly, a Gaussian mixture implementation of the PHD filter is presented under a linear Gaussian model assumption. The results of numerical experiments demonstrate that the proposed approach can achieve a better performance in tracking systems with an unknown newborn target intensity.

• Journal of Advanced Navigation Technology
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• v.15 no.6
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• pp.1132-1137
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• 2011

In this paper, we propose Modified Multi CAMShift Algorithm(Modified Multi Continuously Adaptive Mean Shift Algorithm) that extracts skin color area and tracks several human body parts for real-time human tracking system. Skin color area is extracted by filtering input image in predefined RGB value range. These areas are initial search windows of hands and face for tracking. Gaussian background model prevents search window expending because it restricts skin color area. Also when occluding between these areas, we give more weights in occlusion area and move mass center of target area in color probability distribution image. As result, the proposed algorithm performs better than the original CAMShift approach in multiple object tracking and even when occluding of objects with similar colors.

• Journal of Ocean Engineering and Technology
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• v.28 no.5
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• pp.429-439
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• 2014

The target echoes contain information on the target such as the orientation, kinematics, and internal structure, as well as the external geometrical shape of the target. In addition, the pattern of the target echoes depends on the arrangement of the transmitters and receivers in space. Therefore, the study of the target echoes in a multi-static SONAR system can be useful for detecting and tracking submerged objects using an underwater surveillance system. For this purpose, an acoustic measuring system for multi-static target echoes was designed and tested in an acoustic water tank. Some preliminary data are presented and discussed.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.6
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• pp.141-152
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• 2011

Growing efforts and interests of security techniques in a diverse surveillance environment, the intelligent surveillance system, which is capable of automatically detecting and tracking target objects in multi-cameras environment, is actively developing in a security community. In this paper, we propose an effective visual surveillance system that is avaliable to track objects continuously in multiple non-overlapped cameras. The proposed object tracking scheme consists of object tracking module and tracking management module, which are based on hand-off scheme and protocol. The object tracking module, runs on IP camera, provides object tracking information generation, object tracking information distribution and similarity comparison function. On the other hand, the tracking management module, runs on video control server, provides realtime object tracking reception, object tracking information retrieval and IP camera control functions. The proposed object tracking scheme allows comprehensive framework that can be used in a diverse range of application, because it doesn't rely on the particular surveillance system or object tracking techniques.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2339-2355
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• 2021

In this paper, a joint probabilistic data association algorithm based on loss function (LJPDA) is proposed so that the computation load and accuracy of the multi-target tracking algorithm can be guaranteed simultaneously. Firstly, data association is divided in to three cases based on the relationship among validation gates and the number of measurements in the overlapping area for validation gates. Also the contribution coefficient is employed for evaluating the contribution of a measurement to a target, and the loss function, which reflects the cost of the new proposed data association algorithm, is defined. Moreover, the equation set of optimal contribution coefficient is given by minimizing the loss function, and the optimal contribution coefficient can be attained by using the Newton-Raphson method. In this way, the weighted value of each target can be achieved, and the data association among measurements and tracks can be realized. Finally, we compare performances of LJPDA proposed and joint probabilistic data association (JPDA) algorithm via numerical simulations, and much attention is paid on real-time performance and estimation error. Theoretical analysis and experimental results reveal that the LJPDA algorithm proposed exhibits small estimation error and low computation complexity.

• Smart Media Journal
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• v.4 no.1
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• pp.16-24
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• 2015

In this paper, we propose a method for multi-touch tracking using MRF-based particle filters and gesture likelihood estimation Each touch (of one finger) is considered to be one object. One of frequently occurring issues is the hijacking problem which means that an object tracker can be hijacked by neighboring object. If a predicted particle is close to an adjacent object then the particle's weight should be lowered by analysing the influence of neighboring objects for avoiding hijacking problem. We define a penalty function to lower the weights of those particles. MRF is a graph representation where a node is the location of a target object and an edge describes the adjacent relation of target object. It is easy to utilize MRF as data structure of adjacent objects. Moreover, since MRF graph representation is helpful to analyze multi-touch gestures, we describe how to define gesture likelihoods based on MRF. The experimental results show that the proposed method can avoid the occurrence of hijacking problems and is able to estimate gesture likelihoods with high accuracy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.8
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• pp.1840-1847
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• 2003

In this paper, we have developed the MHDA scheme for data association. This scheme is important in providing a computationally feasible alternative to complete enumeration of JPDA which is intractable. We have proved that given an artificial measurement and track's configuration, MHDA scheme converges to a proper plot in a finite number of iterations. Also, a proper plot which is not the global solution can be corrected by re­initializing one or more times. In this light, even if the performance is enhanced by using the MHDA, we also note that the difficulty in tuning the parameters of the MHDA is critical aspect of this scheme. The difficulty cat however, be overcome by developing suitable automatic instruments that will iteratively verify convergence as the network parameters vary.

• Journal of the Institute of Convergence Signal Processing
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• v.1 no.2
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• pp.138-144
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• 2000

This paper introduced a scheme for finding an optimal association matrix that represents the relationships between the measurements and tracks in multi-target tracking of Radar system. We considered the relationships between targets and measurements as MRF and assumed a priori of the associations as a Gibbs distribution. Based on these assumptions, it was possible to reduce the MAP estimate of the association matrix to the energy minimization problem. After then, we defined an energy function over the measurement space, that may incorporate most of the important natural constraints.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.2
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• pp.198-206
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• 2013

This paper presents the improvement of tracking performance using fuzzy inference system based task prioritizations for multi-function radars. The presented technique calculates elemental priorities using track information of a target and obtain the total priority from fuzzy inference system of each fuzzy set's membership function. In this paper, we proposed the task prioritization algorithms based on fuzzy inference system, and evaluated the tracking performance on multi-function radar scenario using it. As a result, we confirmed that excellent performance could be achieved when using the proposed algorithm.