• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1159-1166
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• 2010

Today, detecting the location of moving object has been traced as various methods in our world. In this paper, we preset the system to improve the estimation accuracy utilizing detail localization using radar sensor based on WSN and situational awareness for a calibration (context aware) database, Rail concept. A variety of existing location tracking method has a problem with receiving of data and accuracy as tracking methodology, and since these located data are the only data to be collected for location tracing, the context aware or monitering as the surrounding environment is limited. So, in this paper, we enhanced the distance aware accuracy using radar sensor utilizing the Doppler effect among the distance measuring method, estimated the location using the Triangulation algorithm. Also, since we composed the environment data(temperature, illuminancem, humidity, noise) to entry of the database, it can be utilized in location-based service according to the later action information inference and positive context decision. In order to verify the validity of the suggested method, we give a few random situation and built test bed of designed node, and over the various test we proved the utilizing the context information through route tracking of moving and data processing.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.3
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• pp.249-255
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• 2007

Under the situation of a fire, it is difficult for a rescue robot to use sensors such as vision sensor, ultrasonic sensor or laser distance sensor because of diffusion, refraction or block of light and sound by dense smoke. But, braille blocks that are installed for the visaully impaired at public places such as subway stations can be used as a map for autonomous mobile robot's localization and navigation. In this paper, we developed a laser sensor stan device which can detect braille blcoks in spite of dense smoke and integrated the device to the robot developed to carry out rescue mission in various hazardous disaster areas at KIST. We implemented MCL algorithm for robot's attitude estimation according to the scanned data and transformed a braille block map to a topological map and designed a nonlinear path tracking controller for autonomous navigation. From various simulations and experiments, we could verify that the developed laser sensor device and the proposed localization method are effective to autonomous tracking of braille blocks and the autonomous navigation robot system can be used for rescue under fire.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.1
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• pp.19-25
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• 2013

In this paper, we proposed an enhanced monopulse MIMO radar system for the tactical scenario where the ground receivers are connected wireless backhaul and closely spaced. By applying the ${\alpha}{\beta}$ filter to the conventional monopulse MIMO radar, we show that the localization performance can be improved significantly. We also propose an efficient localization algorithm for a system with lower rate feedback. Using numerical simulations, we demonstrate that the proposed scheme can improve the localization performance while reducing the feedback over conventional scheme.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.67-90
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• 2019

Accurate detection, tracking and analysis of human movement using robots and other visual surveillance systems is still a challenge. Efforts are on to make the system robust against constraints such as variation in shape, size, pose and occlusion. Traditional methods of detection used the sliding window approach which involved scanning of various sizes of windows across an image. This paper concentrates on employing a state-of-the-art, hierarchical graph based method for segmentation. It has two stages: part level segmentation for color-consistent segments and object level segmentation for category-consistent regions. The tracking phase is achieved by employing SIFT keypoint descriptor based technique in a combined matching and tracking scheme with validation phase. Localization of human region in each frame is performed by keypoints by casting votes for the center of the human detected region. As it is difficult to avoid incorrect keypoints, a consensus-based framework is used to detect voting behavior. The designed methodology is tested on the video sequences having 3 to 4 persons.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.136-141
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• 2009

This paper proposed a framework for handover method in continuously tracking a person of interest across cooperative pan-tilt-zoom (PTZ) cameras. The algorithm here is based on a robust non-parametric technique for climbing density gradients to find the peak of probability distributions called the mean shift algorithm. Most tracking algorithms use only one cue (such as color). The color features are not always discriminative enough for target localization because illumination or viewpoints tend to change. Moreover the background may be of a color similar to that of the target. In our proposed system, the continuous person tracking across cooperative PTZ cameras by mean shift tracking that using color and shape histogram to be feature distributions. Color and shape distributions of interested person are used to register the target person across cameras. For the first camera, we select interested person for tracking using skin color, cloth color and boundary of body. To handover tracking process between two cameras, the second camera receives color and shape cues of a target person from the first camera and using linear color calibration to help with handover process. Our experimental results demonstrate color and shape feature in mean shift algorithm is capable for continuously and accurately track the target person across cameras.

• Journal of information and communication convergence engineering
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• v.10 no.4
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• pp.390-395
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• 2012

This paper describes an implementation of automatic mutual localization of swarm robots using a particle filter. Each robot determines the location of the other robots using wireless sensors. The measured data will be used for determination of the movement method of the robot itself. It also affects the other robots' self-arrangement into formations such as circles and lines. We discuss the problem of a circle formation enclosing a target that moves. This method is the solution for enclosing an invader in a circle formation based on mutual localization of the multi-robot without infrastructure. We use trilateration, which does require knowing the value of the coordinates of the reference points. Therefore, specifying the enclosure point based on the number of robots and their relative positions in the coordinate system. A particle filter is used to improve the accuracy of the robot's location. The particle filter is operates better for mutual location of robots than any other estimation algorithms. Through the experiments, we show that the proposed scheme is stable and works well in real environments.

• Journal of the Semiconductor & Display Technology
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• v.10 no.2
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• pp.31-38
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• 2011

This paper introduces a video based traffic monitoring system for detecting vehicles and obstacles on the road. To segment moving objects from image sequence, we adopt the background subtraction algorithm based on the local binary patterns (LBP). Recently, LBP based texture analysis techniques are becoming popular tools for various machine vision applications such as face recognition, object classification and so on. In this paper, we adopt an extension of LBP, called the Diagonal LBP (DLBP), to handle the background subtraction problem arise in vision-based autonomous parking systems. It reduces the code length of LBP by half and improves the computation complexity drastically. An edge based shadow removal and blob merging procedure are also applied to the foreground blobs, and a pose estimation technique is utilized for calculating the position and heading angle of the moving object precisely. Experimental results revealed that our system works well for real-time vehicle localization and tracking applications.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2780-2782
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• 2005

In this paper, we present a mobile robot localization solution by using a Ubiquitous Vision System (UVS). The collective information gathered by multiple cameras that are strategically placed has many advantages. For example, aggregation of information from multiple viewpoints reduces the uncertainty about the robots' positions. We construct UVS as a multi-agent system by regarding each vision sensor as one vision agent (VA). Each VA performs target segmentation by color and motion information as well as visual tracking for multiple objects. Our modified identified contractnet (ICN) protocol is used for communication between VAs to coordinate multitask. This protocol raises scalability and modularity of thesystem because of independent number of VAs and needless calibration. Furthermore, the handover between VAs by using ICN is seamless. Experimental results show the robustness of the solution with respect to a widespread area. The performance in indoor environments shows the feasibility of the proposed solution in real-time.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.150-157
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• 2009

In this paper, we propose a person tracking based multi-channel audio panning system for multi-view broadcasting services. Multi-view broadcasting is to render the video sequences that are captured from a set of cameras based on different viewpoints, and multi-channel audio panning techniques are necessary for audio rendering in these services. In order to apply such a realistic audio technique to this multi-view broadcasting service, person tracking techniques which are to estimate the position of users are also necessary. For these reasons, proposed methods are composed of two parts. The first part is a person tracking method by using ultrasonic satellites and receiver. We could obtain user's coordinates of high resolution and short duration about 10 mm and 150 ms. The second part is MPEG Surround parameter-based multi-channel audio panning method. It is a method to obtain panned multi-channel audio by controlling the MPEG Surround spatial parameters. A MUSHRA test is conducted to objectively evaluate the perceptual quality and measure localization performance using a dummy head. From the experiments, it is shown that the proposed method provides better perceptual quality and localization performance than the conventional parameter-based audio panning method. In addition, we implement the prototype of person tracking based multi-view broadcasting system by integrating proposed methods with multi-view display system.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.532-537
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• 2009

The necessity of intelligent surveillance system is gradually considered seriously from the space where the security is important. In this paper, we embodied unmanned intelligent system by developing embedded mobile robot based on images and sounds tracking. For objects tracking, we used block-matching algorithm and for sound source tracking, we calculated time differences and magnitude dissimilarities of sound. And we demonstrated the superiority of intruder tracking algorithm through the embodiment of Pan-Tilt camera and sound source tracking module using system, Network camera and mobile robot using system and mobile robot using system. By linking security system, the suggested system can provide some interfacing functions for the security service of the public facilities as well as that of home.