• Title/Summary/Keyword: 인공 시각

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A Study on the Design and Implementation of Multi-Disaster Drone System Using Deep Learning-Based Object Recognition and Optimal Path Planning (딥러닝 기반 객체 인식과 최적 경로 탐색을 통한 멀티 재난 드론 시스템 설계 및 구현에 대한 연구)

  • Kim, Jin-Hyeok;Lee, Tae-Hui;Han, Yamin;Byun, Heejung
    • KIPS Transactions on Computer and Communication Systems
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    • v.10 no.4
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    • pp.117-122
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    • 2021
  • In recent years, human damage and loss of money due to various disasters such as typhoons, earthquakes, forest fires, landslides, and wars are steadily occurring, and a lot of manpower and funds are required to prevent and recover them. In this paper, we designed and developed a disaster drone system based on artificial intelligence in order to monitor these various disaster situations in advance and to quickly recognize and respond to disaster occurrence. In this study, multiple disaster drones are used in areas where it is difficult for humans to monitor, and each drone performs an efficient search with an optimal path by applying a deep learning-based optimal path algorithm. In addition, in order to solve the problem of insufficient battery capacity, which is a fundamental problem of drones, the optimal route of each drone is determined using Ant Colony Optimization (ACO) technology. In order to implement the proposed system, it was applied to a forest fire situation among various disaster situations, and a forest fire map was created based on the transmitted data, and a forest fire map was visually shown to the fire fighters dispatched by a drone equipped with a beam projector. In the proposed system, multiple drones can detect a disaster situation in a short time by simultaneously performing optimal path search and object recognition. Based on this research, it can be used to build disaster drone infrastructure, search for victims (sea, mountain, jungle), self-extinguishing fire using drones, and security drones.

Analysis of Development Characteristics of the Terra Nova Bay Polynya in East Antarctica by Using SAR and Optical Images (SAR와 광학 영상을 이용한 동남극 Terra Nova Bay 폴리냐의 발달 특성 분석)

  • Kim, Jinyeong;Kim, Sanghee;Han, Hyangsun
    • Korean Journal of Remote Sensing
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    • v.38 no.6_1
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    • pp.1245-1255
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    • 2022
  • Terra Nova Bay polynya (TNBP) is a representative coastal polynya in East Antarctica, which is formed by strong katabatic winds. As the TNBP is one of the major sea ice factory in East Antarctica and has a great impact on regional ocean circulation and surrounding marine ecosystem, it is very important to analyze its area change and development characteristics. In this study, we detected the TNBP from synthetic aperture radar (SAR) and optical images obtained from April 2007 to April 2022 by visually analyzing the stripes caused by the Langmuir circulation effect and the boundary between the polynya and surrounding sea ice. Then, we analyzed the area change and development characteristics of the TNBP. The TNBP occurred frequently but in a small size during the Antarctic winter (April-July) when strong katabatic winds blow, whereas it developed in a large size in March and November when sea ice thickness is thin. The 12-hour mean wind speed before the satellite observations showed a correlation coefficient of 0.577 with the TNBP area. This represents that wind has a significant effect on the formation of TNBP, and that other environmental factors might also affect its development process. The direction of TNBP expansion was predominantly determined by the wind direction and was partially influenced by the local ocean current. The results of this study suggest that the influences of environmental factors related to wind, sea ice, ocean, and atmosphere should be analyzed in combination to identify the development characteristics of TNBP.

Training Performance Analysis of Semantic Segmentation Deep Learning Model by Progressive Combining Multi-modal Spatial Information Datasets (다중 공간정보 데이터의 점진적 조합에 의한 의미적 분류 딥러닝 모델 학습 성능 분석)

  • Lee, Dae-Geon;Shin, Young-Ha;Lee, Dong-Cheon
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.40 no.2
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    • pp.91-108
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    • 2022
  • In most cases, optical images have been used as training data of DL (Deep Learning) models for object detection, recognition, identification, classification, semantic segmentation, and instance segmentation. However, properties of 3D objects in the real-world could not be fully explored with 2D images. One of the major sources of the 3D geospatial information is DSM (Digital Surface Model). In this matter, characteristic information derived from DSM would be effective to analyze 3D terrain features. Especially, man-made objects such as buildings having geometrically unique shape could be described by geometric elements that are obtained from 3D geospatial data. The background and motivation of this paper were drawn from concept of the intrinsic image that is involved in high-level visual information processing. This paper aims to extract buildings after classifying terrain features by training DL model with DSM-derived information including slope, aspect, and SRI (Shaded Relief Image). The experiments were carried out using DSM and label dataset provided by ISPRS (International Society for Photogrammetry and Remote Sensing) for CNN-based SegNet model. In particular, experiments focus on combining multi-source information to improve training performance and synergistic effect of the DL model. The results demonstrate that buildings were effectively classified and extracted by the proposed approach.

A Study on the Cognitive Judgment of Pedestrian Risk Factors Using a Second-hand Mobile Phones (중고스마트폰 업사이클링을 통한 보행위험요인 인지판단 연구)

  • Chang, IlJoon;Jeong, Jongmo;Lee, Jaeduk;Ahn, Se-young
    • The Journal of the Korea Contents Association
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    • v.22 no.1
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    • pp.274-282
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    • 2022
  • In order to secure pedestrians' right to walk, we have up-cycled second hand mobile phones to overcome limitations of the existing survey methods, analysis methods, and diagnosis to reduce pedestrian traffic accidents. Second hand mobile phones were up-cycled to produce mobile CCTVs and installed in areas where pedestrian deaths rate is high to secure image data sets for the period of more than 24 hours. It was analyzed by applying image visualization technology and clouding reporting technology, and more precise and accurate results were derived through modeling based on artificial intelligence learning and GIS-based diagnostic guidance. As a result, it was possible to analyze the risk factors and number of pedestrian safety, and even factors that were not known in the existing method could be derived. In addition, the traffic accident risk index was derived by converting data into one year to verify whether second hand mobile phone up-cycling mobile CCTV will be an objective tool for finding pedestrian risk factors. Up-cycling mobile CCTV of second hand mobile phones newly applied through research can be used as a new tool to find pedestrian risk factors, and it can be used as a service to protect the safety of the traffic vulnerable other than pedestrians.

Hiker Mobility Model and Mountain Distress Simulator for Location Estimation of Mountain Distress Victim (산악 조난자의 위치추정을 위한 이동성 모델 및 조난 시뮬레이터)

  • Kim, Hansol;Cho, Yongkyu;Jo, Changhyuk
    • Journal of the Korea Society for Simulation
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    • v.31 no.3
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    • pp.55-61
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    • 2022
  • Currently police and fire departments use a Network/Wifi/GPS based emergency location positioning system established by mobile carriers to directly link with the device of the people who request the rescue to accurately position the expected location in the call area. However in the case of mountain rescue it is difficult to rescue the victim in golden time because the location of the search area cannot be limited when the victim is located in a radio shadow area of the mountain or the device power is off and this situation become worse if victim fail to report 911 by himself due to the injury. In this paper, we are expected to solve the previous problem by propose the mobile telecommunication forensic simulator consist of time series of cell information, human mobility model which include some general and specific features (age, gender, behavioral characteristics of victim, etc.) and intelligent infer system. The results of analysis appear in heatmap of polygons on the map based on the probability of the expected location information of the victim. With this technology we are expected to contribute to rapid and accurate lifesaving by reducing the search area of rescue team.

AI Art Creation Case Study for AI Film & Video Content (AI 영화영상콘텐츠를 위한 AI 예술창작 사례연구)

  • Jeon, Byoungwon
    • The Journal of the Convergence on Culture Technology
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    • v.7 no.2
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    • pp.85-95
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    • 2021
  • Currently, we stand between computers as creative tools and computers as creators. A new genre of movies, which can be called a post-cinema situation, is emerging. This paper aims to diagnose the possibility of the emergence of AI cinema. To confirm the possibility of AI cinema, it was examined through a case study whether the creation of a story, narrative, image, and sound, which are necessary conditions for film creation, is possible by artificial intelligence. First, we checked the visual creation of AI painting algorithms Obvious, GAN, and CAN. Second, AI music has already entered the distribution stage in the market in cooperation with humans. Third, AI can already complete drama scripts, and automatic scenario creation programs using big data are also gaining popularity. That said, we confirmed that the filmmaking requirements could be met with AI algorithms. From the perspective of Manovich's 'AI Genre Convention', web documentaries and desktop documentaries, typical trends post-cinema, can be said to be representative genres that can be expected as AI cinemas. The conditions for AI, web documentaries and desktop documentaries to exist are the same. This article suggests a new path for the media of the 4th Industrial Revolution era through research on AI as a creator of post-cinema.

Evaluation of Debonding Defects in Railway Concrete Slabs Using Shear Wave Tomography (전단파 토모그래피를 활용한 철도 콘크리트 궤도 슬래브 층분리 결함 평가)

  • Lee, Jin-Wook;Kee, Seong-Hoon;Lee, Kang Seok
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.26 no.3
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    • pp.11-20
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    • 2022
  • The main purpose of this study is to investigate the applicability of the shear wave tomography technology as a non-destructive testing method to evaluate the debonding between the track concrete layer (TCL) and the hydraulically stabilized based course (HSB) of concrete slab tracks for the Korea high-speed railway system. A commercially available multi-channel shear wave measurement device (MIRA) is used to evaluate debonding defects in full-scaled mock-up test specimen that was designed and constructed according to the Rheda 200 system. A part of the mock-up specimen includes two artificial debonding defects with a length and a width of 400mm and thicknesses of 5mm and 10mm, respectively. The tomography images obtained by a MIRA on the surface of the concrete specimens are effective for visualizing the debonding defects in concrete. In this study, a simple image processing method is proposed to suppress the noisy signals reflected from the embedded items (reinforcing steel, precast sleeper, insert, etc.) in TCL, which significantly improves the readability of debonding defects in shear wave tomography images. Results show that debonding maps constructed in this study are effective for visualizing the spatial distribution and the depths of the debondiing defects in the railway concrete slab specimen.

A study of artificial neural network for in-situ air temperature mapping using satellite data in urban area (위성 정보를 활용한 도심 지역 기온자료 지도화를 위한 인공신경망 적용 연구)

  • Jeon, Hyunho;Jeong, Jaehwan;Cho, Seongkeun;Choi, Minha
    • Journal of Korea Water Resources Association
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    • v.55 no.11
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    • pp.855-863
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    • 2022
  • In this study, the Artificial Neural Network (ANN) was used to mapping air temperature in Seoul. MODerate resolution Imaging Spectroradiomter (MODIS) data was used as auxiliary data for mapping. For the ANN network topology optimizing, scatterplots and statistical analysis were conducted, and input-data was classified and combined that highly correlated data which surface temperature, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), time (satellite observation time, Day of year), location (latitude, hardness), and data quality (cloudness). When machine learning was conducted only with data with a high correlation with air temperature, the average values of correlation coefficient (r) and Root Mean Squared Error (RMSE) were 0.967 and 2.708℃. In addition, the performance improved as other data were added, and when all data were utilized the average values of r and RMSE were 0.9840 and 1.883℃, which showed the best performance. In the Seoul air temperature map by the ANN model, the air temperature was appropriately calculated for each pixels topographic characteristics, and it will be possible to analyze the air temperature distribution in city-level and national-level by expanding research areas and diversifying satellite data.

Personalized Speech Classification Scheme for the Smart Speaker Accessibility Improvement of the Speech-Impaired people (언어장애인의 스마트스피커 접근성 향상을 위한 개인화된 음성 분류 기법)

  • SeungKwon Lee;U-Jin Choe;Gwangil Jeon
    • Smart Media Journal
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    • v.11 no.11
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    • pp.17-24
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    • 2022
  • With the spread of smart speakers based on voice recognition technology and deep learning technology, not only non-disabled people, but also the blind or physically handicapped can easily control home appliances such as lights and TVs through voice by linking home network services. This has greatly improved the quality of life. However, in the case of speech-impaired people, it is impossible to use the useful services of the smart speaker because they have inaccurate pronunciation due to articulation or speech disorders. In this paper, we propose a personalized voice classification technique for the speech-impaired to use for some of the functions provided by the smart speaker. The goal of this paper is to increase the recognition rate and accuracy of sentences spoken by speech-impaired people even with a small amount of data and a short learning time so that the service provided by the smart speaker can be actually used. In this paper, data augmentation and one cycle learning rate optimization technique were applied while fine-tuning ResNet18 model. Through an experiment, after recording 10 times for each 30 smart speaker commands, and learning within 3 minutes, the speech classification recognition rate was about 95.2%.

The Cultural Meanings of the first optical insturment, Camera obscura, in the pre-modern Age (최초의 영상기구, 카메라 옵스쿠라의 문화사적 의미)

  • LEE, Sang-Myon
    • Korean Association for Visual Culture
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    • v.16
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    • pp.131-161
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    • 2010
  • This thesis investigates the cultural meanings of the first optical instrument, Camera obscura, in the pre-modern age, while it explains the development as well as the use of the Camera obscura in Europe and Korea. For this purpose the thesis traces the significant phases of the historical developments of the Camera obscura from L. da Vinci, G. B. della Porta, D. Barbaro, A. Kircher to J. Zahn etc. The Camera obscura was not only the symbolic instrument of the modernism in the sense that human being wanted to observe the outer world by himself and to be freed from the viewpoint of the christianity, but also was the forerunner of the modern visual culture, because it first time reproduced the artificial image of the natural world. Since the second half of the 17th century the box-type reflex Camera obscura had been produced, it began to be used as aid to drawing for painters like J. Vermeer, A. Canaletto and J. Reynolds etc. throughout Europe. It tells the evidence of the close relation between art and technology in the pre-modern age. Around the end of the 18th century the Camera obscura was brought to Korea, the closed country of the Fareast, by the scholars of the so-called 'Realist school' (Silhak-pa) who went to Beijing to acquire knowledges on the Western science from the European priests. In 1780s Yak-yong JUNG, one of the representative scholars of the Realist school, experimented the Camera obscura, and then, it was used for sketches of higher aristocrats' portraits by the supreme portrait painter of that time, Myoung-ki LEE. Those were possible only under the reign of the culturally liberal and reformative King, Jung-jo (ruled 1776-1800), and after his retreatment the inquiry of the Camera obscura had been dimished. It is not a historical coincidence that the Camera obscura could be examined and used in the period of the Enlightment both in Europe and Korea.