• Title/Summary/Keyword: Convex-hull

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Development of Low Cost Autonomous-Driving Delivery Robot System Using SLAM Technology (SLAM 기술을 활용한 저가형 자율주행 배달 로봇 시스템 개발)

  • Donghoon Lee;Jehyun Park;Kyunghoon Jung
    • IEMEK Journal of Embedded Systems and Applications
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    • v.18 no.5
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    • pp.249-257
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    • 2023
  • This paper discusses the increasing need for autonomous delivery robots due to the current growth in the delivery market, rising delivery fees, high costs of hiring delivery personnel, and the need for contactless services. Additionally, the cost of hardware and complex software systems required to build and operate autonomous delivery robots is high. To provide a low-cost alternative to this, this paper proposes a autonomous delivery robot platform using a low-cost sensor combination of 2D LIDAR, depth camera and tracking camera to replace the existing expensive 3D LIDAR. The proposed robot was developed using the RTAB-Map SLAM open source package for 2D mapping and overcomes the limitations of low-cost sensors by using the convex hull algorithm. The paper details the hardware and software configuration of the robot and presents the results of driving experiments. The proposed platform has significant potential for various industries, including the delivery and other industries.

3D Pose Recognition using Body Silhouette Image (실루엣 영상을 이용한 삼차원 인체 포즈인식)

  • Oh, Chi-Min;Kim, Min-Uk;Lee, Chil-Woo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2008.05a
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    • pp.11-12
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    • 2008
  • 본 논문은 이차원 영상에 투영된 삼차원 인체의 포즈를 인식하기 위하여 이차원 영상에 투영된 인체의 실루엣 정보를 이용하였다. 인체는 삼차원 공간에서 움직이므로 이차원 영상으로 모든 정보를 알아내기에는 부족한 면이 있다. 따라서 본 논문에서는 인체 포즈의 주시 방향을 결정한 후 인체의 실루엣 영상 Convex-hull 특징점 정보를 이용하여 인체의 삼차원 포즈를 인식하였다. 인체의 포즈는 PCA로 차원을 축소하였으며 Diffusion Distance로 데이터베이스의 포즈모델 중 가장 가까운 모델을 선택하였다.

Marker Detection by Using Affine-SIFT Matching Points for Marker Occlusion of Augmented Reality (증강현실에서 가려진 마커를 위한 Affine-SIFT 정합 점들을 이용한 마커 검출 기법)

  • Kim, Yong-Min;Park, Chan-Woo;Park, Ki-Tae;Moon, Young-Shik
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.48 no.2
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    • pp.55-65
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    • 2011
  • In this paper, a novel method of marker detection robust against marker occlusion in augmented reality is proposed. the proposed method consists of four steps. In the first step, in order to effectively detect an occluded marker, we first utilize the Affine-SIFT (ASIFT, Affine-Scale Invariant Features Transform) for detecting matching points between an enrolled marker and an input images with an occluded marker. In the second step, we apply the Principal Component Analysis (PCA) for eliminating outlier of the matching points in the enrolled marker. And then matching points are projected to the first and second axis for longest value and the shortest value of an ellipse are determined by average distance between the projected points and a center of the points. In the third step, Convex-hull vertices including matching points are considered as polygon vertices for estimating a geometric affine transformation. In the final step, by estimating the geometric affine transformation of the points, a marker robust against a marker occlusion is detected. Experimental results have shown that the proposed method effectively detects occlude markers.

An Experimental Study on the Effect of Adoption of Special Rudders on Course Stability of a Ship (특수타의 채택이 침로 안정성에 미치는 영향에 관한 실험적 연구)

  • Sohn, K.H.;Kim, J.H.;Kim, H.S.;Kim, Y.S.;Ha, M.K.
    • Journal of the Society of Naval Architects of Korea
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    • v.34 no.3
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    • pp.27-37
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    • 1997
  • The paper deals with the effectiveness of various special rudders on course stability of a ship. We adopted five types of rudder, such as one normal rudder and four special rudders, which contain two rudders with concave and convex strips on sides respectively, one flapped rudder, and one rudder with end plates on tips. In the circulating water channel, model test was carried out for measuring lift characteristics of the rudders in open water. And various captive model tests were also carried out for measuring the experimental constants related with helm angle and steering in hull-propeller-rudder system. From the test results, the changes in manoeuvring hydrodynamic derivatives due to adoption of normal and special rudders were predicted. Then course stability performances of a ship with normal and special rudders were evaluated and discussed. As a result, it is clarified that the rudder with concave or convex strips and flapped rudder have no effect on course stability, while the rudder with end plates improves course stability with effect. The result in this study is expected to be used usefully when the course stability is in issue and has to be improved without amendment of hull design at initial design phase or after construction of a ship.

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Hierarchical Browsing Interface for Geo-Referenced Photo Database (위치 정보를 갖는 사진집합의 계층적 탐색 인터페이스)

  • Lee, Seung-Hoon;Lee, Kang-Hoon
    • Journal of the Korea Computer Graphics Society
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    • v.16 no.4
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    • pp.25-33
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    • 2010
  • With the popularization of digital photography, people are now capturing and storing far more photos than ever before. However, the enormous number of photos often discourages the users to identify desired photos. In this paper, we present a novel method for fast and intuitive browsing through large collections of geo-referenced photographs. Given a set of photos, we construct a hierarchical structure of clusters such that each cluster includes a set of spatially adjacent photos and its sub-clusters divide the photo set disjointly. For each cluster, we pre-compute its convex hull and the corresponding polygon area. At run-time, this pre-computed data allows us to efficiently visualize only a fraction of the clusters that are inside the current view and have easily recognizable sizes with respect to the current zoom level. Each cluster is displayed as a single polygon representing its convex hull instead of every photo location included in the cluster. The users can quickly transfer from clusters to clusters by simply selecting any interesting clusters. Our system automatically pans and zooms the view until the currently selected cluster fits precisely into the view with a moderate size. Our user study demonstrates that these new visualization and interaction techniques can significantly improve the capability of navigating over large collections of geo-referenced photos.

Trunk Stabilization Measurements Using the Nintendo Wii (닌텐도 위를 활용한 흉부 흔들림의 자세 안정성 측정)

  • Yang, Juyeong;Yoo, Jaeha;Kim, Dongyon;Park, Junmo;Kim, Soochan
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.7
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    • pp.239-247
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    • 2014
  • The CTSIB (Clinical Test of Sensory Integration on Balance) using high sensitive pressure sensors is normally used to assess the sense of balance in hospital. It takes an objective measurement of the amount of sway that occurs in the body trunk by observing the change in the center of pressure (CoP) on the foot at the upright posture. In this paper, we would like to propose method to easily measure trunk sway in home. Although the Wii balance board(WBB) is used for games, it can measures the center of pressure, which is highly correlated. The Wii remote controller(WRC) is inexpensive compared to the WBB, but it has problems with estimation of trunk sway because it can't measure pressure directly like WBB. We collected data from 10 normal subjects (5 males, 5 females) from two devices in order to compare the CoP from WBB and the center of mass (CoM) from WRC. The results of WRC and WBB was similar when the data were analyzed by the convex hull and ellipse area.

Automated Areal Feature Matching in Different Spatial Data-sets (이종의 공간 데이터 셋의 면 객체 자동 매칭 방법)

  • Kim, Ji Young;Lee, Jae Bin
    • Journal of Korean Society for Geospatial Information Science
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    • v.24 no.1
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    • pp.89-98
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    • 2016
  • In this paper, we proposed an automated areal feature matching method based on geometric similarity without user intervention and is applied into areal features of many-to-many relation, for confusion of spatial data-sets of different scale and updating cycle. Firstly, areal feature(node) that a value of inclusion function is more than 0.4 was connected as an edge in adjacency matrix and candidate corresponding areal features included many-to-many relation was identified by multiplication of adjacency matrix. For geometrical matching, these multiple candidates corresponding areal features were transformed into an aggregated polygon as a convex hull generated by a curve-fitting algorithm. Secondly, we defined matching criteria to measure geometrical quality, and these criteria were changed into normalized values, similarity, by similarity function. Next, shape similarity is defined as a weighted linear combination of these similarities and weights which are calculated by Criteria Importance Through Intercriteria Correlation(CRITIC) method. Finally, in training data, we identified Equal Error Rate(EER) which is trade-off value in a plot of precision versus recall for all threshold values(PR curve) as a threshold and decided if these candidate pairs are corresponding pairs or not. To the result of applying the proposed method in a digital topographic map and a base map of address system(KAIS), we confirmed that some many-to-many areal features were mis-detected in visual evaluation and precision, recall and F-Measure was highly 0.951, 0.906, 0.928, respectively in statistical evaluation. These means that accuracy of the automated matching between different spatial data-sets by the proposed method is highly. However, we should do a research on an inclusion function and a detail matching criterion to exactly quantify many-to-many areal features in future.

Hand Region Tracking and Fingertip Detection based on Depth Image (깊이 영상 기반 손 영역 추적 및 손 끝점 검출)

  • Joo, Sung-Il;Weon, Sun-Hee;Choi, Hyung-Il
    • Journal of the Korea Society of Computer and Information
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    • v.18 no.8
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    • pp.65-75
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    • 2013
  • This paper proposes a method of tracking the hand region and detecting the fingertip using only depth images. In order to eliminate the influence of lighting conditions and obtain information quickly and stably, this paper proposes a tracking method that relies only on depth information, as well as a method of using region growing to identify errors that can occur during the tracking process and a method of detecting the fingertip that can be applied for the recognition of various gestures. First, the closest point of approach is identified through the process of transferring the center point in order to locate the tracking point, and the region is grown from that point to detect the hand region and boundary line. Next, the ratio of the invalid boundary, obtained by means of region growing, is used to calculate the validity of the tracking region and thereby judge whether the tracking is normal. If tracking is normal, the contour line is extracted from the detected hand region and the curvature and RANSAC and Convex-Hull are used to detect the fingertip. Lastly, quantitative and qualitative analyses are performed to verify the performance in various situations and prove the efficiency of the proposed algorithm for tracking and detecting the fingertip.

Image Processing and Deep Learning Techniques for Fast Pig's Posture Determining and Head Removal (돼지의 빠른 자세 결정과 머리 제거를 위한 영상처리 및 딥러닝 기법)

  • Ahn, Hanse;Choi, Wonseok;Park, Sunhwa;Chung, Yongwha;Park, Daihee
    • KIPS Transactions on Software and Data Engineering
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    • v.8 no.11
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    • pp.457-464
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    • 2019
  • The weight of pig is one of the main factors in determining the health and growth state of pigs, their shipment, the breeding environment, and the ration of feed, and thus measuring the pig's weight is an important issue in productivity perspective. In order to estimate the pig's weight by using the number of pig's pixels from images, acquired from a Top-view camera, the posture determining and the head removal from images are necessary to measure the accurate number of pixels. In this research, we propose the fast and accurate method to determine the pig's posture by using a fast image processing technique, find the head location by using a fast deep learning technique, and remove pig's head by using light weighted image processing technique. First, we determine the pig's posture by comparing the length from the center of the pig's body to the outline of the pig in the binary image. Then, we train the location of pig's head, body, and hip in images using YOLO(one of the fast deep learning based object detector), and then we obtain the location of pig's head and remove an outside area of head by using head location. Finally, we find the boundary of head and body by using Convex-hull, and we remove pig's head. In the Experiment result, we confirmed that the pig's posture was determined with an accuracy of 0.98 and a processing speed of 250.00fps, and the pig's head was removed with an accuracy of 0.96 and a processing speed of 48.97fps.

Fast 3D mesh generation using projection for line laser-based 3D Scanners (라인 레이저 기반 3차원 스캐너에서 투영을 이용한 고속 3D 메쉬 생성)

  • Lee, Kyungme;Yoo, Hoon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.20 no.3
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    • pp.513-518
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    • 2016
  • This paper presents a fast 3D mesh generation method using projection for line laser-based 3D scanners. The well-known method for 3D mesh generation utilizes convex hulls for 4D vertices that is converted from the input 3D vertices. This 3D mesh generation for a large set of vertices requires a lot of time. To overcome this problem, the proposed method takes (${\theta}-y$) 2D depth map into account. The 2D depth map is a projection version of 3D data with a form of (${\theta}$, y, z) which are intermediately acquired by line laser-based 3D scanners. Thus, our 2D-based method is a very fast 3D mesh generation method. To evaluate our method, we conduct experiments with intermediate 3D vertex data from line-laser scanners. Experimental results show that the proposed method is superior to the existing method in terms of mesh generation speed.