• Title/Summary/Keyword: Localization Algorithm

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Implementation of Emergency Evacuation Support System in Panic-type Disaster (돌발성 재해에 대비한 긴급 피난 지원 시스템의 구현)

  • Hwang, Jun-Su;Choi, Young-Bok
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.20 no.7
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    • pp.1269-1276
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    • 2016
  • Recently, natural disasters including earthquakes, tsunamis, floods, and snowstorms, in addition to disasters of human origin such as arson, and acts of terror, have caused numerous injuries and fatalities around the world. During such disasters, victims need to obtain information such as the exact location of the disaster and appropriate evacuation routes in order to relocate to safe areas. In this study, We propose the algorithm for Emergency Rescue Evacuation Support System(ERESS). In case a emergency disaster occurs, ERESS is possible to detect it quickly using through the movement of people. The mobile terminal analyzes behavior and location of indoor pedestrian. And it sends the result to the server. The server determines whether an emergency situation occurred or not based on the received transmission information. When an emergency situation occurs, the server will notify it to the mobile terminal. Then, indoor pedestrian conduct emergency evacuation using mobile terminal.

A Speaker Detection System based on Stereo Vision and Audio (스테레오 시청각 기반의 화자 검출 시스템)

  • An, Jun-Ho;Hong, Kwang-Seok
    • Journal of Internet Computing and Services
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    • v.11 no.6
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    • pp.21-29
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    • 2010
  • In this paper, we propose the system which detects the speaker, who is speaking currently, among a number of users. A proposed speaker detection system based on stereo vision and audio is mainly composed of the followings: a position estimation of speaker candidates using stereo camara and microphone, a current speaker detection, and a speaker information acquisition based on a mobile device. We use the haar-like features and the adaboost algorithm to detect the faces of speaker candidates with stereo camera, and the position of speaker candidates is estimated by a triangulation method. Next, the Time Delay Of Arrival (TDOA) is estimated by the Cross Power Spectrum Phase (CPSP) analysis to find the direction of source with two microphone. Finally we acquire the information of the speaker including his position, voice, and face by comparing the information of the stereo camera with that of two microphone. Furthermore, the proposed system includes a TCP client/server connection method for mobile service.

A Study on Eyelid and Eyelash Localization for Iris Recognition (홍채 인식에서의 눈꺼풀 및 눈썹 추출 연구)

  • Kang, Byung-Joon;Park, Kang-Ryoung
    • Journal of Korea Multimedia Society
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    • v.8 no.7
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    • pp.898-905
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    • 2005
  • Iris recognition Is that identifies a user based on the unique iris muscle patterns which has the functionalities of dilating or contracting pupil region. Because it is reported that iris recognition is more accurate than other biometries such as face, fingerprint, vein and speaker recognition, iris recognition is widely used in the high security application domain. However, if unnecessary information such as eyelid and eyelash is included in iris region, the error for iris recognition is increased, consequently. In detail, if iris region is used to generate iris code including eyelash and eyelid, the iris codes are also changed and the error rate is increased. To overcome such problem, we propose the method of detecting eyelid by using pyramid searching parabolic deformable template. In addition, we detect the eyelash by using the eyelash mask. Experimental results show that EER(Equal Error Rate) for iris recognition using the proposed algorithm is lessened as much as $0.3\%$ compared to that not using it.

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A Stable Access Point Selection Method Considering RSSI Variation in Fingerprinting for Indoor Positioning (실내측위를 위한 핑거프린팅에서의 RSSI 변동을 고려한 안정된 AP 선출방법)

  • Hwang, DongYeop;Kim, Kangseok
    • KIPS Transactions on Computer and Communication Systems
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    • v.6 no.9
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    • pp.369-376
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    • 2017
  • Recently, an RSSI-based fingerprinting localization technology has been widely used in indoor location-based services. In the conventional fingerprinting method, as many APs as possible are used to increase the accuracy of location estimation. In another study, a part of APs having the strongest RSSI signal intensity are selected and used to reduce the time spent for positioning. However, it does not reflect the influence of RSSI occurred from the changes of the surrounding environments such as human movement or moving obstacles in a real environment. The environmental changes may cause the difference between the predicted RSSI signal strength value and the measured value, and thus occur an unpredictable error in the position estimation. Therefore, in order to mitigate the error caused by environmental factors, it is necessary to select APs suitable for indoor positioning estimation considering the changes in the surrounding environments. In this paper, we propose a method to select stable APs considering the influence of surrounding environments and derive a suitable positioning algorithm. In addition, we compare and analyze the performance of the proposed method with that of the existing AP selection methods through experiments.

Position Estimation of MBK system for non-Gaussian Underwater Sensor Networks (비가우시안 노이즈가 존재하는 수중 환경에서 MBK 시스템의 위치 추정)

  • Lee, Dae-Hee;Yang, Yeon-Mo;Huh, Kyung Moo
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.1
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    • pp.232-238
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    • 2013
  • This paper study the position estimation of MBK system according to the non-linear filter for non-Gaussian noise in underwater sensor networks. In the filter to estimate location, recently, the extended Kalman filter (EKF) and particle filter are getting attention. EKF is widely used due to the best algorithm in the Gaussian noise environment, but has many restrictions on the usage in non-Gaussian noise environment such as in underwater. In this paper, we propose the improved One-Dimension Particle Filter (ODPF) using the distribution re-interpretation techniques based on the maximum likelihood. Through the simulation, we compared and analyzed the proposed particle filter with the EKF in non-Gaussian underwater sensor networks. In the case of both the sufficient statistical sample and the sufficient calculation capacity, we confirm that the ODPF's result shows more accurate localization than EKF's result.

Implementation of a Coded Aperture Imaging System for Gamma Measurement and Experimental Feasibility Tests

  • Kim, Kwangdon;Lee, Hakjae;Jang, Jinwook;Chung, Yonghyun;Lee, Donghoon;Park, Chanwoo;Joung, Jinhun;Kim, Yongkwon;Lee, Kisung
    • IEIE Transactions on Smart Processing and Computing
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    • v.6 no.1
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    • pp.66-70
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    • 2017
  • Radioactive materials are used in medicine, non-destructive testing, and nuclear plants. Source localization is especially important during nuclear decommissioning and decontamination because the actual location of the radioactive source within nuclear waste is often unknown. The coded-aperture imaging technique started with space exploration and moved into X-ray and gamma ray imaging, which have imaging process characteristics similar to each other. In this study, we simulated $21{\times}21$ and $37{\times}37$ coded aperture collimators based on a modified uniformly redundant array (MURA) pattern to make a gamma imaging system that can localize a gamma-ray source. We designed a $21{\times}21$ coded aperture collimator that matches our gamma imaging detector and did feasibility experiments with the coded aperture imaging system. We evaluated the performance of each collimator, from 2 mm to 10 mm thicknesses (at 2 mm intervals) using root mean square error (RMSE) and sensitivity in a simulation. In experimental results, the full width half maximum (FWHM) of the point source was $5.09^{\circ}$ at the center and $4.82^{\circ}$ at the location of the source was $9^{\circ}$. We will continue to improve the decoding algorithm and optimize the collimator for high-energy gamma rays emitted from a nuclear power plant.

Design and Implementation of Multi-Sensor-based Vehicle Localization and Tracking System (멀티센서 기반 차량 위치인식 시스템의 설계 및 구현)

  • Jang, Yoon-Ho;Nam, Sang-Kyoon;Bae, Sang-Jun;Sung, Tae-Kyung;Kwak, Kyung-Sup
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.8 no.6
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    • pp.121-130
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    • 2009
  • In this paper, Gaussian probability distribution model based multi-sensor data fusion algorithm is proposed for a vehicular location awareness system. Conventional vehicular location awareness systems are operated by GPS (Global Positioning System). However, the conventional system is not working in the indoor of building or urban area where the receiver is difficult to receive the signal from satellites. A method which is combined GPS and UWB (Ultra Wide-Band) has developed to improve this problem. However, vehicular is difficult to receive seamless location information since the measurement systems by both GPS and UWB convert the vehicle's movement information separately at each sensor. In this paper, normalized probability distribution model based Hybrid UWB/GPS is proposed by utilizing GPS location data and UWB sensor data. Therefore the proposed system provides information with seamless and location flexible properties. The proposed system tested by Ubisense and Asen GPS in the $12m{\times}8m$ outdoor environments. As a result, the proposed system has improved performance for accurateness and connection ability between devices to support various CNS (Car Navigation System).

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Performance Enhancement of Face Detection Algorithm using FLD (FLD를 이용한 얼굴 검출 알고리즘의 성능 향상)

  • Nam, Mi-Young;Kim, Kwang-Baek
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.6
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    • pp.783-788
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    • 2004
  • Many reported methods assume that the faces in an image or an image sequence have been identified and localization. Face detection from image is a challenging task because of the variability in scale, location, orientation and pose. The difficulties in visual detection and recognition are caused by the variations in viewpoint, viewing distance, illumination. In this paper, we present an efficient linear discriminant for multi-view face detection and face location. We define the training data by using the Fisher`s linear discriminant in an efficient learning method. Face detection is very difficult because it is influenced by the poses of the human face and changes in illumination. This idea can solve the multi-view and scale face detection problems. In this paper, we extract the face using the Fisher`s linear discriminant that has hierarchical models invariant size and background. The purpose of this paper is to classify face and non-face for efficient Fisher`s linear discriminant.

Determination of Target Position with BRW Stereoatic Frame in non-orthogonal CT scans (비직교성 전산화단층촬영에서 뇌정위수술용 좌표계를 이용한 표적위치 결정)

  • Park, Tae-Jin;Kim, Ok-Bae;Son, Eun-Ik
    • Progress in Medical Physics
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    • v.3 no.1
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    • pp.53-62
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    • 1992
  • Stereotactic implantation of intracranial lesions, and the development of stereotactic convergent irradiation, radiosurgery, techniques have to obtain the accurate coordinates of the tumor locations and that of critical organ. Computed tomography(CT) provides relatively precise imformations of tumor localization and surround the normal organs for conventional radiotherapy. This CT image use to extend for stereotactic radiosurgery procedures. Since the convergent irradiation technique in linear accelerator requires the target center coincident with gantry isocenter or radosurgery frame, the target coordinates must be described in accurately. We used the BRW stereotactic system for describing the target position in CT images This algorithm provides the coordinate conversions for orthogonal or non-orthogonal CT scan image. In this experiments, the target positions have shown the small discripancy within :to.3mm uncertanty in several known target positions in the phantom through the provided programs and it compared to that of BRW stereotactic systems.

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Development and Evaluation of Maximum-Likelihood Position Estimation with Poisson and Gaussian Noise Models in a Small Gamma Camera

  • Chung, Yong-Hyun;Park, Yong;Song, Tae-Yong;Jung, Jin-Ho;Gyuseong Cho
    • Proceedings of the Korean Society of Medical Physics Conference
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    • 2002.09a
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    • pp.331-334
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    • 2002
  • It has been reported that maximum-likelihood position-estimation (MLPE) algorithms offer advantages of improved spatial resolution and linearity over conventional Anger algorithm in gamma cameras. The purpose of this study is to evaluate the performances of the noise models, Poisson and Gaussian, in MLPE for the localization of photons in a small gamma camera (SGC) using NaI(Tl) plate and PSPMT. The SGC consists of a single NaI(Tl) crystal, 10 cm diameter and 6 mm thick, optically coupled to a PSPMT (Hamamatsu R3292-07). The PSPMT was read out using a resistive charge divider, which multiplexes 28(X) by 28(Y) cross wire anodes into four channels. Poisson and Gaussian based MLPE methods have been implemented using experimentally measured light response functions. The system resolutions estimated by Poisson and Gaussian based MLPE were 4.3 mm and 4.0 mm, respectively. Integral uniformities were 29.7% and 30.6%, linearities were 1.5 mm and 1.0 mm and count rates were 1463 cps and 1388 cps in Poisson and Gaussian based MLPE, respectively. The results indicate that Gaussian based MLPE, which is convenient to implement, has better performances and is more robust to statistical noise than Poisson based MLPE.

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