• ETRI Journal
• /
• v.42 no.1
• /
• pp.54-66
• /
• 2020

Nowadays, the broad availability of cameras and embedded systems makes the application of computer vision very promising as a supporting technology for intelligent transportation systems, particularly in the field of vehicle tracking. Although there are several existing trackers, the limitation of using low-cost cameras, besides the relatively low processing power in embedded systems, makes most of these trackers useless. For the tracker to work under those conditions, the video frame rate must be reduced to decrease the burden on computation. However, doing this will make the vehicle seem to move faster on the observer's side. This phenomenon is called the fast motion challenge. This paper proposes a tracker called dynamic swarm particle (DSP), which solves the challenge. The term particle refers to the particle filter, while the term swarm refers to particle swarm optimization (PSO). The fundamental concept of our method is to exploit the continuity of vehicle dynamic motions by creating dynamic models based on PSO. Based on the experiments, DSP achieves a precision of 0.896 and success rate of 0.755. These results are better than those obtained by several other benchmark trackers.

• Journal of Institute of Control, Robotics and Systems
• /
• v.5 no.5
• /
• pp.585-592
• /
• 1999

A new paradigm of technology, based on the overall interactions of technology, human and environment, is explored. History of technology and machines is reviewed in terms of the interactions of human and machines. Two main concepts of intelligent interactions proposed, holism and embodiment, are based on the interactions of machines and human through human body : Korperlichkeit ( corporeality). Human body movements are the result of long periods of evolution and, thus, are very optimized motions. Complicated and flexible motions could be easily achieved by mimicking human body movements. Motion capture and mimic systems based on the electromagnetic, visual, and gyroscopic type trackers, are being implemented to demonstrate these concepts. Also, various motion mappings are investigated on these interactive systems. By exploring a new paradigm of technology through Korperlichkeit, an oriental view of technology as relativities may evolve to embrace the limitations of western view of machines as an absolute independent form.

• Structural Engineering and Mechanics
• /
• v.78 no.5
• /
• pp.519-528
• /
• 2021

One of the most efficient designs of solar trackers for photovoltaic panels is the single-axis tracker, which holds the panels along a torque tube that is driven by a motor at the central section. These trackers have evolved to become extremely slender structures due to mechanical optimization against static load and the need of cost reduction in a very competitive market. Owing to the corresponding decrease in mechanical resistance, some of these trackers have suffered aeroelastic instability even at moderate wind speeds, leading to catastrophic failures. In the present work, an analytical and experimental approach has been developed to study that phenomenon. The analytical study has led to identify the dimensionless parameters that govern the motion of the panel-tracker structure. Also, systematic wind tunnel experiments have been carried out on a 3D aeroelastic scale model. The tests have been successful in reproducing the aeroelastic phenomena arising in real-scale cases and have allowed the identification and a close characterization of the phenomenon. The main results have been the determination of the critical velocity for torsional galloping as a function of tilt angle and a calculation methodology for the optimal sizing of solar tracker shafts.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.2
• /
• pp.693-709
• /
• 2018

In this paper, we propose a compact Convolutional Neural Network (CNN)-based tracker in conjunction with a particle filter architecture, in which the CNN model operates as an accurate candidates estimator, while the particle filter predicts the target motion dynamics, lowering the overall number of calculations and refines the resulting target bounding box. Experiments were conducted on the Online Object Tracking Benchmark (OTB) [34] dataset and comparison analysis in respect to other state-of-art has been performed based on accuracy and precision, indicating that the proposed algorithm outperforms all state-of-the-art trackers included in the OTB dataset, specifically, TLD [16], MIL [1], SCM [36] and ASLA [15]. Also, a comprehensive speed performance analysis showed average frames per second (FPS) among the top-10 trackers from the OTB dataset [34].

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.9
• /
• pp.4438-4460
• /
• 2017

The Kernelized Correlation Filters (KCF) tracker has caused the extensive concern in recent years because of the high efficiency. Numerous improvements have been made successively. However, due to the abrupt motion between the consecutive image frames, these methods cannot track object well. To cope with the problem, we propose an extended KCF tracker based on swarm intelligence method. Unlike existing KCF-based trackers, we firstly introduce a swarm-based sampling method to KCF tracker and design a unified framework to track smooth or abrupt motion simultaneously. Secondly, we propose a global motion estimation method, where the exploration factor is constructed to search the whole state space so as to adapt abrupt motion. Finally, we give an adaptive threshold in light of confidence map, which ensures the accuracy of the motion estimation strategy. Extensive experimental results in both quantitative and qualitative measures demonstrate the effectiveness of our proposed method in tracking abrupt motion.

• International Journal of Aeronautical and Space Sciences
• /
• v.11 no.3
• /
• pp.206-220
• /
• 2010

This paper proposes optimal control techniques for determining translational and rotational maneuvers that facilitate proximity operations and docking. Two candidate controllers that provide translational motion are compared. A state-dependent Riccati equation controller is formulated from nonlinear relative motion dynamics, and a linear quadratic tracking controller is formulated from linearized relative motion. A linear quadratic Gaussian controller using star trackers to provide quaternion measurements is designed for precision attitude maneuvering. The attitude maneuvers are evaluated for different final axis alignment geometries that depend on the approach distance. A six degrees-of-freedom simulation demonstrates that the controllers successfully perform proximity operations that meet the conditions for docking.

• 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.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2020.07a
• /
• pp.703-704
• /
• 2020

본 논문에서는 4차 산업혁명의 화두인 가상현실 기술을 활용하여 현대인들의 단조로운 생활패턴과 운동부족을 보완하기 위해 두다리에 착용한 트래커들을 이용하여 다리의 움직임을 인식하여 가상현실에 적용한 러닝 게임을 설계하게 하였고, 이를 구현하여 1인칭 시점 가상현실 게임 콘텐츠를 개발하였다. 게임 콘텐츠는 가상현실 HMD장비와 연동되는 트래커를 착용하여 진행하며 트래커 장비를 이용하여 사용자의 두 다리의 움직임을 더욱 정확하게 인식할 수 있다. 게임 안에서의 최고기록 갱신을 통해 사용자는 더욱 게임에 몰입감을 가지고 갱신을 위하여 플레이 하다 보면 활동량의 증가로 칼로리 소모와 근육을 증가 시킬 수 있다.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.11 no.4
• /
• pp.219-225
• /
• 2016

Visual object tracking is one of the key tasks in computer vision. Robust trackers should address challenging issues such as fast motion, deformation, occlusion and so on. In this paper, we therefore propose a visual object tracking method that exploits inter-frame correlations of convolutional feature maps in Convolutional Neural Net (ConvNet). The proposed method predicts the location of a target by considering inter-frame spatial correlation between target location proposals in the present frame and its location in the previous frame. The experimental results show that the proposed algorithm outperforms the state-of-the-art work especially in hard-to-track sequences.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2012.07a
• /
• pp.269-270
• /
• 2012

Features which exhibit scale and rotation invariance, such as SIFT, are notorious for expensive computation time, and often overlooked for real-time tracking scenarios. This paper proposes a descriptorless matching algorithm based on motion vectors between consecutive frames to find the geometrically closest candidate to each tracked reference feature in the database. Descriptor-less matching forgoes expensive SIFT descriptor extraction without loss of matching accuracy and exhibits dramatic speed-up compared to traditional, naive matching based trackers. Descriptor-less SIFT tracking runs in real-time on an Intel dual core machine at an average of 24 frames per second.