• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.11
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• pp.68-78
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• 1999

A new algorithm for tracking feature points in an image sequence is presented. Most existing feature tracking algorithms often produce false trajectories, because the matching measures do not precisely reflect motion characteristics. In this paper, three attributes including spatial coordinate, motion direction and motion magnitude are used to calculate the feature point correspondence. The trajectories of feature points are determined by calculation the matching measure, which is defined as the minimum weighted Euclidean distance between two feature points. The weights of the attributes are updated reflecting the motion characteristics, so that the robust tracking of feature points is achieved. The proposed algorithm can find the trajectories correctly which has been shown by experimental results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1464-1480
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• 2019

Robust tracking of infrared (IR) pedestrian targets with various backgrounds, e.g. appearance changes, illumination variations, and background disturbances, is a great challenge in the infrared image processing field. In the paper, we address a new tracking method for IR pedestrian targets via multi-feature local sparse representation (SR), which consists of three important modules. In the first module, a multi-feature local SR model is constructed. Considering the characterization of infrared pedestrian targets, the gray and edge features are first extracted from all target templates, and then fused into the model learning process. In the second module, an effective tracker is proposed via the learned model. To improve the computational efficiency, a sliding window mechanism with multiple scales is first used to scan the current frame to sample the target candidates. Then, the candidates are recognized via sparse reconstruction residual analysis. In the third module, an adaptive dictionary update approach is designed to further improve the tracking performance. The results demonstrate that our method outperforms several classical methods for infrared pedestrian tracking.

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.247-256
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• 2022

Visual tracking of selected target objects is fundamental challenging problems in computer vision. Object tracking localize the region of target object with bounding box in the video. We propose a Siam-FPN based custom fully CNN to solve visual tracking problems by regressing the target area in an end-to-end manner. A method of preserving the feature information flow using a feature map connection structure was applied. In this way, information is preserved and emphasized across the network. To regress object region and to classify object, the region proposal network was connected with the Siamese network. The performance of the tracking algorithm was evaluated using the OTB-100 dataset. Success Plot and Precision Plot were used as evaluation matrix. As a result of the experiment, 0.621 in Success Plot and 0.838 in Precision Plot were achieved.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.2
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• pp.36-44
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• 2009

In this paper, we suggest a system of detecting a vehicle with lane violation, which can detect the vehicle with lane violation, by using the feature point tracking. The whole algorithm in the suggested system of detecting a vehicle with lane violation is composed of three stages such as feature extraction, register and tracking in feature for the tracking-targeted vehicle, and detecting a vehicle with lane violation. In the stage of feature extraction, the feature is extracted from the inputted image by sing the feature-extraction algorithm available for the real-time processing. The extracted features are again selected the racking-targeted feature. The registered feature is tracked by using NCC(normalized cross correlation). Finally, whether or not lane violation is finally detected by using information on the tracked features. As a result of experimenting the suggested system by using the acquired image in the section with a ban on intervention, the excellent performance was shown with 99.09% for positive recognition ratio and 0.9% for error ratio. The fast processing speed could be obtained in 34.48 frames per second available for real-time processing.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.8
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• pp.81-87
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• 1999

In general, feature detection and tracking algorithms is classified by EBGM using Garbor-jet, NNC-R and STK algorithm using pixel eigenvalue. In those algorithms, EBGM and NCC-R detect features with feature model, but STK algorithm has a characteristics of an automatic feature selection. In this paper, to solve the initial problem of NR tracking in STK algorithm, we detected features using STK algorithm in modelled feature region and tracked features with NR method. In tracking, to improve the tracking accuracy for features by NR method, we proposed BMA-NR method. We evaluated that BMA-NR method was superior to NBMA-NR in that feature tracking accuracy, since BMA-NR method was able to solve the local minimum problem due to search window size of NR.

• ETRI Journal
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• v.39 no.2
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• pp.151-162
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• 2017

With the remarkable growth in rich media in recent years, people are increasingly exposed to visual information from the environment. Visual information continues to play a vital role in rich media because people's real interests lie in dynamic information. This paper proposes a novel discrete dynamic swarm optimization (DDSO) algorithm for video object tracking using invariant features. The proposed approach is designed to track objects more robustly than other traditional algorithms in terms of illumination changes, background noise, and occlusions. DDSO is integrated with a matching procedure to eliminate inappropriate feature points geographically. The proposed novel fitness function can aid in excluding the influence of some noisy mismatched feature points. The test results showed that our approach can overcome changes in illumination, background noise, and occlusions more effectively than other traditional methods, including color-tracking and invariant feature-tracking methods.

• Journal of Korea Multimedia Society
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• v.19 no.5
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• pp.890-900
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• 2016

This paper presents a multiple target tracking system using target feature information. In the proposed system, the state of target is defined as its kinematic as well as feature : the kinematic includes a location and a velocity; the feature contains the image correlation between a prior target and a current measurement. The feature information is used for generating the validation matrix and association probability of joint probabilistic data association (JPDA) algorithm. Through the Kalman filter, the target kinematic is updated. Then the tracking information is cycled by the track management algorithm. The system has been evaluated using the images obtained from Electro-Optics/ InfraRed (EO/IR) sensor. It is verified that the proposed system can reduce the complexity burden of JPDA process and can enhance the track maintenance rate.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.07a
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• pp.297-298
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• 2013

본 논문에서는 IR 영상추적을 위하여 가린 표적의 실제 중심을 예측하는 추적창 조절(target window adjustment) 기법을 제시한다. 대표적 분할 추적(patch tracking) 방식인 특징점 추적(feature point tracking)은 표적의 중심과 특징점을 coupling하여 가린 표적의 실제 중심을 예측할 수 있으나, 형상 정보가 적은 영상에서 표적의 ROI(Region of Interest)는 특징점의 분포만으로는 구할 수 없다. 본 논문에서는 상관추적의 추적창 조절 기법과 특징점 추적의 coupling 기법을 결합하여 표적이 장애물에 가리는 경우에도 안정적인 추적창을 유지한다.

• Journal of the Korea Society of Computer and Information
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• v.22 no.5
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• pp.21-28
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• 2017

As technology related to digital imaging equipment is developed and generalized, digital imaging system is used for various purposes in fields of society. The object tracking technology from digital image data in real time is one of the core technologies required in various fields such as security system and robot system. Among the existing object tracking technologies, cam shift technology is a technique of tracking an object using color information of an object. Recently, digital image data using infrared camera functions are widely used due to various demands of digital image equipment. However, the existing cam shift method can not track objects in image data without color information. Our proposed tracking algorithm tracks the object by analyzing the color if valid color information exists in the digital image data, otherwise it generates the lightness feature information and tracks the object through it. The brightness feature information is generated from the ratio information of the width and the height of the area divided by the brightness. Experimental results shows that our tracking algorithm can track objects in real time not only in general image data including color information but also in image data captured by an infrared camera.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.3011-3024
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• 2021

Pose estimation of the sensor is important issue in many applications such as robotics, navigation, tracking, and Augmented Reality. This paper proposes visual-inertial integration system appropriate for dynamically moving condition of the sensor. The orientation estimated from Inertial Measurement Unit (IMU) sensor is used to calculate the essential matrix based on the intrinsic parameters of the camera. Using the epipolar geometry, the outliers of the feature point matching are eliminated in the image sequences. The pose of the sensor can be obtained from the feature point matching. The use of IMU sensor can help initially eliminate erroneous point matches in the image of dynamic scene. After the outliers are removed from the feature points, these selected feature points matching relations are used to calculate the precise fundamental matrix. Finally, with the feature point matching relation, the pose of the sensor is estimated. The proposed procedure was implemented and tested, comparing with the existing methods. Experimental results have shown the effectiveness of the technique proposed in this paper.