• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.4
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• pp.682-691
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• 2017

In this paper, we propose the fusion design methodology of both pedestrian detection and object tracking system realized with the aid of HOG-PCA based RBFNN pattern classifier. The proposed system includes detection and tracking parts. In the detection part, HOG features are extracted from input images for pedestrian detection. Dimension reduction is also dealt with in order to improve detection performance as well as processing speed by using PCA which is known as a typical dimension reduction method. The reduced features can be used as the input of the FCM-based RBFNNs pattern classifier to carry out the pedestrian detection. FCM-based RBFNNs pattern classifier consists of condition, conclusion, and inference parts. FCM clustering algorithm is used as the activation function of hidden layer. In the conclusion part of network, polynomial functions such as constant, linear, quadratic and modified quadratic are regarded as connection weights and their coefficients of polynomial function are estimated by LSE-based learning. In the tracking part, object tracking algorithms such as mean shift(MS) and cam shift(CS) leads to trace one of the pedestrian candidates nominated in the detection part. Finally, INRIA person database is used in order to evaluate the performance of the pedestrian detection of the proposed system while MIT pedestrian video as well as indoor and outdoor videos obtained from IC&CI laboratory in Suwon University are exploited to evaluate the performance of tracking.

• The Journal of Korea Robotics Society
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• v.11 no.4
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• pp.205-216
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• 2016

The localization of the robot is one of the most important factors of navigating mobile robots. The use of featured information of landmarks is one approach to estimate the location of the robot. This approach can be classified into two categories: the natural-landmark-based and artificial-landmark-based approach. Natural landmarks are suitable for any environment, but they may not be sufficient for localization in the less featured or dynamic environment. On the other hand, artificial landmarks may generate shaded areas due to space constraints. In order to improve these disadvantages, this paper presents a novel development of the localization system by using artificial and natural-landmarks-based approach on a topological map. The proposed localization system can recognize far or near landmarks without any distortion by using landmark tracking system based on top-view image transform. The camera is rotated by distance of landmark. The experiment shows a result of performing position recognition without shading section by applying the proposed system with a small number of artificial landmarks in the mobile robot.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.335-345
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• 2017

Recently, location systems using RFID technology have been studied in indoor environments. However, the existing techniques require high computational cost to compute the location of a moving object because they compare the location proximity of all reference tags and objects. In this paper, we propose an RFID based location positioning scheme using event filtering, which reduces the computation cost of calculating the locations of moving objects while maintaining the accuracy of location estimation. In addition, we propose an incremental location update policy to reduce the location update cost for moving objects. We also compare the proposed scheme with one of the localization schemes, LANDMARC using a performance evaluation. As a result, the proposed scheme outperforms LANDMARC in terms of the computational cost of location estimation. The proposed scheme also reduces the cost of location update by using the RFID-based update policy.

• Journal of information and communication convergence engineering
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• v.19 no.3
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• pp.161-165
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• 2021

Since the first commercialization of beacon-based services in 2011, various services have been provided to improve Bluetooth performance, and research has been conducted to accurately recognize user locations using beacons. The various measurement methods of indoor positioning systems (IPS) include methods using receiver signal strength indicator (RSSI) the strength of which varies greatly in accuracy depending on whether there are obstacles such as cement walls or doors. In this paper, we present a method to provide accurate positioning services even in the presence of obstacles in indoor spaces. To this end, we connect the HM-10 module supporting the beacon with Arduino Uno, to place beacons in three directions in real-world indoor space, and derive an optimal trilateration equation. Based on the derivation, we select the optimal expression for calculating the distance between the beacon and the moving station and use it to verify the coordinate determination for the moving station.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.2
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• pp.466-474
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• 2014

According to wireless network technology and mobile processors performance were improved, the small wireless mobile device such as smart phones has been widely utilized. The mobile devices can be used GPS information, thereby the services based on location information was increased. GPS was impossible to provide location information in indoor and signal shading environment, and the tracking systems based on short distance wireless communication are required infrastructure. The IEEE 802.11 based tracking system is possible estimation using APs, however the tracking device is exhausted battery power seriously. In this paper, we propose IEEE 802.11 based low-power tracking system. We reduced power consumption from channel scanning and network connection. For performance evaluation, we designed and implemented the tracking tag device, and measured power consumption of the device. As the simulation result, we confirmed that the power consumption was reduced 46% compare to the standard execution.

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.4
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• pp.241-253
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• 2006

In modem societies, a monitoring system is required to automatically detect and track persons from several cameras scattered in a wide area. Combining multiple cameras with non-overlapping views and a tracking technique, we propose a method that tracks automatically the target persons in one camera and transfers the tracking information to other networked cameras through a server. So the proposed method tracks thoroughly the target persons over the cameras. In this paper, we use a person model to detect and distinguish the corresponding person and to transfer the person's tracking information. A movement of the tracked persons is defined on FOV lines of the networked cameras. The tracked person has 6 statuses. The proposed system was experimented in several indoor scenario. We achieved 91.2% in an averaged tracking rate and 96% in an averaged status rate.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5496-5521
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• 2018

Object detection and tracking is the basic capability of mobile robots to achieve natural human-robot interaction. In this paper, an object tracking system of mobile robot is designed and validated using improved multiple instance learning algorithm. The improved multiple instance learning algorithm which prevents model drift significantly. Secondly, in order to improve the capability of classifiers, an active sample selection strategy is proposed by optimizing a bag Fisher information function instead of the bag likelihood function, which dynamically chooses most discriminative samples for classifier training. Furthermore, we integrate the co-training criterion into algorithm to update the appearance model accurately and avoid error accumulation. Finally, we evaluate our system on challenging sequences and an indoor environment in a laboratory. And the experiment results demonstrate that the proposed methods can stably and robustly track moving object.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.11
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• pp.954-962
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• 2002

In a park or street, we can see many people jogging or walking with their dogs tracking their masters. In this study, an entertainment robot that imitates a dog's behavior is created. The robot's task is tracking a moving target that is recognized as the master. In order to design the robot, the ecological approach. in which the robot's goals and surroundings heavily influence its design, is used. A three-wheel type locomotion system is designed as the robot's physical structure which can follow a human jogging in outdoor space like a park. A sensor system which can detect the position of a master for the robot in the outdoor space, is developed. This sensor system consists of a signal transmitter which is at the hand of a master and some sensors which are mounted on the robot. The transmitter emits RF(radio frequency) and ultrasonic signals and the sensors detect the direction and distance from the robot to the transmitter by using the received signals. For the control architecture of the robot, a purely reactive behavior-based method is used in order to increase speed of response. The developed robot is evaluated through experiments conducted in indoor and outdoor environments.

• The Journal of Korea Robotics Society
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• v.6 no.1
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• pp.86-96
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• 2011

The human-following is one of the significant procedure in human-friendly navigation of mobile robots. There are many approaches of human-following technology. Many approaches have adopted various multiple sensors such as vision system and Laser Range Finder (LRF). In this paper, we propose detection and tracking approaches for human legs by the use of a single LRF. We extract four simple attributes of human legs. To define the boundary of extracted attributes mathematically, we used a Support Vector Data Description (SVDD) scheme. We establish an efficient leg-tracking scheme by exploiting a human walking model to achieve robust tracking under occlusions. The proposed approaches were successfully verified through various experiments.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10d
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• pp.482-487
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• 2007

유비쿼터스 컴퓨팅 애플리케이션은 빈번히 위치 정보를 이용하기 때문에 모바일 노드들의 위치를 파악하여 서비스를 제공해 주는 것이 점차 중요하게 인식되고 있다. 여기서 모바일 노드들의 위치 추정은 센서 네트워크에서 노드들에게 좌표를 할당하는 것과 같은 의미이다. 센서 네트워크 환경에서 모바일 노드 위치 추정을 다루는 연구들이 늘어나고 있으나, 현재 제안된 거의 모든 연구들의 위치 추정 실험에서는 엔코더, 자이로, 가속도 센서 등을 이용해서 실제 이동량을 측정해야만 한다. 이 점에 착안하여, 본 연구에서는 어떤 추가적인 센서를 추가하지 않고 실험에서 얻은 모바일 노드의 좌표들을 카메라로 획득한 실제 영상에 맵핑시킴으로써 위치 추정 실험을 검증하기 위한 방법론을 제시하고, 제안한 방법론을 이용하여 크리켓 실내 위치 시스템(Cricket Indoor Location System)의 대표적인 두 가지 구조인 Active and Passive Infrastructure에서 무인 로봇의 위치 추정 실험 결과를 보여준다.