• Title/Summary/Keyword: Detection map

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Multi-robot Mapping Using Omnidirectional-Vision SLAM Based on Fisheye Images

  • Choi, Yun-Won;Kwon, Kee-Koo;Lee, Soo-In;Choi, Jeong-Won;Lee, Suk-Gyu
    • ETRI Journal
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    • v.36 no.6
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    • pp.913-923
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    • 2014
  • This paper proposes a global mapping algorithm for multiple robots from an omnidirectional-vision simultaneous localization and mapping (SLAM) approach based on an object extraction method using Lucas-Kanade optical flow motion detection and images obtained through fisheye lenses mounted on robots. The multi-robot mapping algorithm draws a global map by using map data obtained from all of the individual robots. Global mapping takes a long time to process because it exchanges map data from individual robots while searching all areas. An omnidirectional image sensor has many advantages for object detection and mapping because it can measure all information around a robot simultaneously. The process calculations of the correction algorithm are improved over existing methods by correcting only the object's feature points. The proposed algorithm has two steps: first, a local map is created based on an omnidirectional-vision SLAM approach for individual robots. Second, a global map is generated by merging individual maps from multiple robots. The reliability of the proposed mapping algorithm is verified through a comparison of maps based on the proposed algorithm and real maps.

Automatic detection of the optimal ejecting direction based on a discrete Gauss map

  • Inui, Masatomo;Kamei, Hidekazu;Umezu, Nobuyuki
    • Journal of Computational Design and Engineering
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    • v.1 no.1
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    • pp.48-54
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    • 2014
  • In this paper, the authors propose a system for assisting mold designers of plastic parts. With a CAD model of a part, the system automatically determines the optimal ejecting direction of the part with minimum undercuts. Since plastic parts are generally very thin, many rib features are placed on the inner side of the part to give sufficient structural strength. Our system extracts the rib features from the CAD model of the part, and determines the possible ejecting directions based on the geometric properties of the features. The system then selects the optimal direction with minimum undercuts. Possible ejecting directions are represented as discrete points on a Gauss map. Our new point distribution method for the Gauss map is based on the concept of the architectural geodesic dome. A hierarchical structure is also introduced in the point distribution, with a higher level "rough" Gauss map with rather sparse point distribution and another lower level "fine" Gauss map with much denser point distribution. A system is implemented and computational experiments are performed. Our system requires less than 10 seconds to determine the optimal ejecting direction of a CAD model with more than 1 million polygons.

Three-dimensional Map Construction of Indoor Environment Based on RGB-D SLAM Scheme

  • Huang, He;Weng, FuZhou;Hu, Bo
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.37 no.2
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    • pp.45-53
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    • 2019
  • RGB-D SLAM (Simultaneous Localization and Mapping) refers to the technology of using deep camera as a visual sensor for SLAM. In view of the disadvantages of high cost and indefinite scale in the construction of maps for laser sensors and traditional single and binocular cameras, a method for creating three-dimensional map of indoor environment with deep environment data combined with RGB-D SLAM scheme is studied. The method uses a mobile robot system equipped with a consumer-grade RGB-D sensor (Kinect) to acquire depth data, and then creates indoor three-dimensional point cloud maps in real time through key technologies such as positioning point generation, closed-loop detection, and map construction. The actual field experiment results show that the average error of the point cloud map created by the algorithm is 0.0045m, which ensures the stability of the construction using deep data and can accurately create real-time three-dimensional maps of indoor unknown environment.

Structural Change Detection Technique for RDF Data in MapReduce (맵리듀스에서의 구조적 RDF 데이터 변경 탐지 기법)

  • Lee, Taewhi;Im, Dong-Hyuk
    • KIPS Transactions on Software and Data Engineering
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    • v.3 no.8
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    • pp.293-298
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    • 2014
  • Detecting and understanding the changes between RDF data is crucial in the evolutionary process, synchronization system, and versioning system on the web of data. However, current researches on detecting changes still remain unsatisfactory in that they did neither consider the large scale of RDF data nor accurately produce the RDF deltas. In this paper, we propose a scalable and effective change detection using a MapReduce framework which has been used in many fields to process and analyze large volumes of data. In particular, we focus on the structure-based change detection that adopts a strategy for the comparison of blank nodes in RDF data. To achieve this, we employ a method which is composed of two MapReduce jobs. First job partitions the triples with blank nodes by grouping each triple with the same blank node ID and then computes the incoming path to the blank node. Second job partitions the triples with the same path and matchs blank nodes with the Hungarian method. In experiments, we show that our approach is more accurate and effective than the previous approach.

Automatic Detection of Objects-of-Interest using Visual Attention and Image Segmentation (시각 주의와 영상 분할을 이용한 관심 객체 자동 검출 기법)

  • Shi, Do Kyung;Moon, Young Shik
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.5
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    • pp.137-151
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    • 2014
  • This paper proposes a method of detecting object of interest(OOI) in general natural images. OOI is subjectively estimated by human in images. The vision of human, in general, might focus on OOI. As the first step for automatic detection of OOI, candidate regions of OOI are detected by using a saliency map based on the human visual perception. A saliency map locates an approximate OOI, but there is a problem that they are not accurately segmented. In order to address this problem, in the second step, an exact object region is automatically detected by combining graph-based image segmentation and skeletonization. In this paper, we calculate the precision, recall and accuracy to compare the performance of the proposed method to existing methods. In experimental results, the proposed method has achieved better performance than existing methods by reducing the problems such as under detection and over detection.

Ship Wake Detection Algorithm for Maritime Optical Images (해양 영상에서 선박으로 인한 후류 영역 탐지 기법)

  • Truong, Mai Thanh Nhat;Lee, Chul
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2019.11a
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    • pp.233-234
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    • 2019
  • We propose a novel algorithm for detecting ship wake trails in optical images of the maritime environment. The proposed algorithm first removes the sky region by localizing the horizon to prevent false wake trails detection. Then, a feature map is computed by employing brightness distortion and chromatic distortion. The feature map is thresholded to obtain a rough estimate of wake trails. Finally, the wake map is refined using the shape prior information. Experimental results show that the proposed algorithm can effectively detect wake trails in images.

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DETECTING LANDSLIDE LOCATION USING KOMSAT 1AND IT'S USING LANDSLIDE-SUSCEPTIBILITY MAPPING

  • Lee, Sa-Ro;Lee, Moung-Jin
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.840-843
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    • 2006
  • The aim of this study was to detect landslide using satellite image and apply the landslide to probabilistic landslide-susceptibility mapping at Gangneung area, Korea using a Geographic Information System (GIS). Landslide locations were identified by change detection technique of KOMSAT-1 (Korea Multipurpose Satellite) EOC (Electro Optical Camera) images and checked in field. For landslide-susceptibility mapping, maps of the topography, geology, soil, forest, lineaments, and land cover were constructed from the spatial data sets. Then, the sixteen factors that influence landslide occurrence were extracted from the database. Using the factors and detected landslide, the relationships were calculated using frequency ratio, one of the probabilistic model. Then, landslide-susceptibility map was drawn using the frequency ration and finally, the map was verified by comparing with existing landslide locations. As the verification result, the prediction accuracy showed 86.76%. The landslide-susceptibility map can be used to reduce hazards associated with landslides and to land cover planning.

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SUBPIXEL UNMIXING TECHNIQUE FOR DETECTION OF USEFUL MINERAL RESOURCES USING HYPERSPECTRAL IMAGERY

  • Hyun, Chang-Uk;Park, Hyeong-Dong
    • Proceedings of the KSRS Conference
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    • 2008.10a
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    • pp.66-67
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    • 2008
  • Most mineral resources are located in subsurface but mineral exploration starts with a step of investigation in wide-area to find evidence of buried ores. Conventional technique for exploration on wide-area as a preliminary survey is an observation using naked eyes by geologist or chemical analysis using lots of samples obtained from target area. Hyperspectral remote sensing can overcome those subjective and time consuming survey and can produce mineral resources distribution map. Precise resource map requires information of mineral distribution in a subpixellevel because mineral is distributed as rock components or narrow veins. But most hyperspectral data is composed of pixels of several meters or more than ten meters scale. We reviewed subpixel unmixing algorithms which have been used for geological field and tested detection ability with Hyperion imagery, geological map and seven spectral curves of mineral and rock specimens which were obtained from study areas.

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Real-Time Stereoscopic Image Conversion Using Motion Detection and Region Segmentation (움직임 검출과 영역 분할을 이용한 실시간 입체 영상 변환)

  • Kwon Byong-Heon;Seo Burm-suk
    • Journal of Digital Contents Society
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    • v.6 no.3
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    • pp.157-162
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    • 2005
  • In this paper we propose real-time cocersion methods that can convert into stereoscopic image using depth map that is formed by motion detection extracted from 2-D moving image and region segmentation separated from image. Depth map which represents depth information of image and the proposed absolute parallax image are used as the measure of qualitative evaluation. We have compared depth information, parallax processing, and segmentation between objects with different depth for proposed and conventional method. As a result, we have confirmed the proposed method can offer realistic stereoscopic effect regardless of direction and velocity of moving object for a moving image.

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