• Title/Summary/Keyword: Real Time Object Detection

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Efficient Tracking System for Passengers with the Detection Algorithm of a Stopping Vehicle (차량정차감지 알고리즘을 이용한 탑승자의 효율적 위치추적시스템)

  • Lee, Byung-Mun;Shin, Hyun-Ho;Kang, Un-Gu
    • Journal of Internet Computing and Services
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    • v.12 no.6
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    • pp.73-82
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    • 2011
  • The location-based service is emerging again to the public attention. The location recognition environment up-to-now has been studied with its focus only on a person, an object or a moving object. However, this study proposes a location recognition model that serves to recognize and track, in real time, multiple passengers in a moving vehicle. Identifying the locations of passengers can be classified into two classes: one is to use the high price terminal with GPS function, and the other is to use the economic price compact terminal without GPS function. Our model enables the simple compact terminal to provide effective location recognition under the on-boarding situation by transmitting messages through an interface device and sensor networks for a vehicle equipped with GPS. This technology reduces transmission traffic after detecting the condition of a vehicle (being parked or running), because it does not require transmission/receiving of information on the locations of passengers who are confined in a vehicle when the vehicle is running. Also it extends battery life by saving power consumption of the compact terminal. Hence, we carried out experiments to verify its serviceability by materializing the efficient tracking system for passengers with the detection algorithm of a stopping vehicle proposed in this study. Moreover, about 200 experiments using the system designed with this technology proved successful recognition on on-boarding and alighting of passengers with the maximum transmission distance of 12 km. In addition to this, the running recognition tests showed the test with the detection algorithm of a stopping vehicle has reduced transmission traffic by 41.6% compared to the algorithm without our model.

Dual CNN Structured Sound Event Detection Algorithm Based on Real Life Acoustic Dataset (실생활 음향 데이터 기반 이중 CNN 구조를 특징으로 하는 음향 이벤트 인식 알고리즘)

  • Suh, Sangwon;Lim, Wootaek;Jeong, Youngho;Lee, Taejin;Kim, Hui Yong
    • Journal of Broadcast Engineering
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    • v.23 no.6
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    • pp.855-865
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    • 2018
  • Sound event detection is one of the research areas to model human auditory cognitive characteristics by recognizing events in an environment with multiple acoustic events and determining the onset and offset time for each event. DCASE, a research group on acoustic scene classification and sound event detection, is proceeding challenges to encourage participation of researchers and to activate sound event detection research. However, the size of the dataset provided by the DCASE Challenge is relatively small compared to ImageNet, which is a representative dataset for visual object recognition, and there are not many open sources for the acoustic dataset. In this study, the sound events that can occur in indoor and outdoor are collected on a larger scale and annotated for dataset construction. Furthermore, to improve the performance of the sound event detection task, we developed a dual CNN structured sound event detection system by adding a supplementary neural network to a convolutional neural network to determine the presence of sound events. Finally, we conducted a comparative experiment with both baseline systems of the DCASE 2016 and 2017.

Real-time Detection Technique of the Target in a Berth for Automatic Ship Berthing (선박 자동접안을 위한 정박지 목표물의 실시간 검출법)

  • Choi, Yong-Woon;;Kim, Young-Bok;Lee, Kwon-Soon
    • Journal of Institute of Control, Robotics and Systems
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    • v.12 no.5
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    • pp.431-437
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    • 2006
  • In this paper vector code correlation(VCC) method and an algorithm to promote the image-processing performance in building an effective measurement system using cameras are described far automatically berthing and controlling the ship equipped with side-thrusters. In order to realize automatic ship berthing, it is indispensable that the berthing assistant system on the ship should continuously trace a target in the berth to measure the distance to the target and the ship attitude, such that we can make the ship move to the specified location. The considered system is made up of 4 apparatuses compounded from a CCD camera, a camera direction controller, a popular PC with a built-in image processing board and a signal conversion unit connected to parallel port of the PC. The object of this paper is to reduce the image-processing time so that the berthing system is able to ensure the safety schedule against risks during approaching to the berth. It could be achieved by composing the vector code image to utilize the gradient of an approximated plane found with the brightness of pixels forming a certain region in an image and verifying the effectiveness on a commonly used PC. From experimental results, it is clear that the proposed method can be applied to the measurement system for automatic ship berthing and has the image-processing time of fourfold as compared with the typical template matching method.

Development of a Tactile Sensor Array with Flexible Structure Using Piezoelectric Film

  • Yu, Kee-Ho;Kwon, Tae-Gyu;Yun, Myung-Jong;Lee, Seong-Cheol
    • Journal of Mechanical Science and Technology
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    • v.16 no.10
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    • pp.1222-1228
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    • 2002
  • This research is the development of a flexible tactile sensor array for service robots using PVDF (polyvinylidene fluoride) film for the detection of a contact state in real time. The prototype of the tactile sensor which has 8${\times}$8 array using PVDF film was fabricated. In the fabrication procedure, the electrode patterns and the common electrode of the thin conductive tape were attached to both sides of the 281$\mu\textrm{m}$ thickness PVDF film using conductive adhesive. The sensor was covered with polyester film for insulation and attached to the rubber base for a stable structure. The proposed fabrication method is simple and easy to make the sensor. The sensor has the advantages in the implementing for practical applications because its structure is flexible and the shape of the each tactile element can be designed arbitrarily. The signals of a contact force to the tactile sensor were sensed and processed in the DSP system in which the signals are digitized and filtered. Finally, the signals were integrated for taking the force profile. The processed signals of the output of the sensor were visualized in a personal computer, and the shape and force distribution of the contact object were obtained. The reasonable performance for the detection of the contact state was verified through the sensing examples.

RHT-Based Ellipse Detection for Estimating the Position of Parts on an Automobile Cowl Cross Bar Assembly (RHT 기법을 이용한 카울크로스바의 조립위치 결정에 관한 연구)

  • Shin, Ik-Sang;Kang, Dong-Hyeon;Hong, Young-Gi;Min, Young-Bong
    • Journal of Biosystems Engineering
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    • v.36 no.5
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    • pp.377-383
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    • 2011
  • This study proposed the new method of discerning the assembled parts and presuming the position of central point in a Cowl Cross Bar (CCB) using a Charge-Couple Device (CCD) camera attached to a robot in the auto assembly line. Three control points of an ellipse were decided by three reference points, which were equally distanced. The radii of these reference points were determined by the size of the object, and the repeated presumption secured the precise determination. The comparison of the central point of ellipse presumed by Randomized Hough Transform (RHT) with the part information stored in a database was used for determining the faulty part in an assembly. The method proposed in this study was applied for the real-time inspection of elliptical parts, such as bolt, nut hole and so on, connected to a CCB using a CCD camera. The findings of this study showed that the precise decision on whether the parts are inferior or not can be made irrespective of the lighting condition of industrial site and the noises of the surface of the part. In addition, the defect decision on the individual elliptic parts assembled in a CCB showed more than 98% accuracy within a 500-millisecond period at most.

A New Efficient Detection Method in Lane Road Environment (도로 환경에 효율적인 새로운 차선 검출 방법)

  • Lee, Kyung-Min;Lin, Chi-Ho
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.17 no.1
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    • pp.129-136
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    • 2018
  • In this paper, we propose a new real-time lane detection method that is efficient for road environment. Existing methods have a problem of low reliability under environmental changes. In order to overcome this problem, we emphasize the lane candidate area by using gray level division. And Extracts a straight line component near the lane by using the Hough transform, and generates an ROI for each straight line based on the extracted coordinates. And integrates the generated ROI images. Then, the lane is determined by dividing the object using the dual queue in the ROI image. The proposed method is able to detect lanes even in the environmental change unlike the conventional method. And It is possible to obtain an advantage that the area corresponding to the background such as sky, mountain, etc. is efficiently removed and high reliability is obtained.

Video Digital Doorlock System for Recognition and Transmission of Approaching Objects (접근객체 인식 및 전송을 위한 영상 디지털 도어락 시스템 설계)

  • Lee, Sang-Rack;Park, Jin-Tae;Woo, Byoung-Hyoun;Choi, Han-Go
    • KIPS Transactions on Software and Data Engineering
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    • v.3 no.6
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    • pp.237-242
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    • 2014
  • Current digital door lock systems are mainly designed for users' convenience, so they have weakness in security. Thus, this paper suggests a video digital doorlock system grouped with a relay device, a server, and a digital doorlock with a camera, sensors, and communication modules, which is detecting or recognizing objects approaching to the front of the door lock system and sending images and door-opening information to users' smart devices. Experiments showed that the suggested system has 96~98% recognition rate of approaching objects and requires 17.1~23.9 seconds for transmission on average, depending on network systems. Therefore, the system is thought to have enough capability for real time security response by monitoring the front area of the doorlock system.

A Study on Automatic Detection of Speed Bump by using Mathematical Morphology Image Filters while Driving (수학적 형태학 처리를 통한 주행 중 과속 방지턱 자동 탐지 방안)

  • Joo, Yong Jin;Hahm, Chang Hahk
    • Journal of Korean Society for Geospatial Information Science
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    • v.21 no.3
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    • pp.55-62
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    • 2013
  • This paper aims to detect Speed Bump by using Omni-directional Camera and to suggest Real-time update scheme of Speed Bump through Vision Based Approach. In order to detect Speed Bump from sequence of camera images, noise should be removed as well as spot estimated as shape and pattern for speed bump should be detected first. Now that speed bump has a regular form of white and yellow area, we extracted speed bump on the road by applying erosion and dilation morphological operations and by using the HSV color model. By collecting huge panoramic images from the camera, we are able to detect the target object and to calculate the distance through GPS log data. Last but not least, we evaluated accuracy of obtained result and detection algorithm by implementing SLAMS (Simultaneous Localization and Mapping system).

Defect Detection of the Wall Thinning Pipe of the Nuclear Power Plant Using Infrared Thermography (적외선열화상을 이용한 원자력발전소 감육 배관의 결함 검출)

  • Kim, Kyeong-Suk;Chang, Ho-Sub;Hong, Dong-Pyo;Park, Chan-Joo;Na, Sung-Won;Kim, Kyung-Su;Jung, Hyun-Chul
    • Journal of the Korean Society for Nondestructive Testing
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    • v.30 no.2
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    • pp.85-90
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    • 2010
  • The infrared energy is emitted in the infrared wavelength range that corresponds to the surface temperature of a object which has temperature that is over the absolute the temperature(OK). The infrared thermography (IRT) is a non-destrnctive testing method that provides thermal video for the user in real-time by converting the infrared quantity that is detected by the infrared detector into temperature. The pipes of nuclear power plant(NPP) could be thinned by the corrosion and fatigue and the defect could lead to a big accident. For this reason, the effective non-destructive testing method is necessary. In this study, the relationship between the measured temperature and the defect depth or size of NPP pipes were recognized and that was applied to detect the wall thinning defects of NPP pipes.

Abnormal behaviour in rock bream (Oplegnathus fasciatus) detected using deep learning-based image analysis

  • Jang, Jun-Chul;Kim, Yeo-Reum;Bak, SuHo;Jang, Seon-Woong;Kim, Jong-Myoung
    • Fisheries and Aquatic Sciences
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    • v.25 no.3
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    • pp.151-157
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    • 2022
  • Various approaches have been applied to transform aquaculture from a manual, labour-intensive industry to one dependent on automation technologies in the era of the fourth industrial revolution. Technologies associated with the monitoring of physical condition have successfully been applied in most aquafarm facilities; however, real-time biological monitoring systems that can observe fish condition and behaviour are still required. In this study, we used a video recorder placed on top of a fish tank to observe the swimming patterns of rock bream (Oplegnathus fasciatus), first one fish alone and then a group of five fish. Rock bream in the video samples were successfully identified using the you-only-look-once v3 algorithm, which is based on the Darknet-53 convolutional neural network. In addition to recordings of swimming behaviour under normal conditions, the swimming patterns of fish under abnormal conditions were recorded on adding an anaesthetic or lowering the salinity. The abnormal conditions led to changes in the velocity of movement (3.8 ± 0.6 cm/s) involving an initial rapid increase in speed (up to 16.5 ± 3.0 cm/s, upon 2-phenoxyethanol treatment) before the fish stopped moving, as well as changing from swimming upright to dying lying on their sides. Machine learning was applied to datasets consisting of normal or abnormal behaviour patterns, to evaluate the fish behaviour. The proposed algorithm showed a high accuracy (98.1%) in discriminating normal and abnormal rock bream behaviour. We conclude that artificial intelligence-based detection of abnormal behaviour can be applied to develop an automatic bio-management system for use in the aquaculture industry.