• 제목/요약/키워드: 3D location algorithm

검색결과 162건 처리시간 0.03초

Decoupled Location Parameter Estimation of 3-D Near-Field Sources in a Uniform Circular Array using the Rank Reduction Algorithm

  • Jung, Tae-Jin;Kwon, Bum-Soo;Lee, Kyun-Kyung
    • 한국음향학회지
    • /
    • 제30권3호
    • /
    • pp.129-135
    • /
    • 2011
  • An algorithm is presented for estimating the 3-D location (i.e., azimuth angle, elevation angle, and range) of multiple sources with a uniform circular array (UCA) consisting of an even number of sensors. Recently the rank reduction (RARE) algorithm for partly-calibrated sensor arrays was developed. This algorithm is applicable to sensor arrays consisting of several identically oriented and calibrated linear subarrays. Assuming that a UCA consists of M sensors, it can be divided into M/2 identical linear subarrays composed of two facing sensors. Based on the structure of the subarrays, the steering vectors are decomposed into two parts: range-independent 2-D direction-of-arrival (DOA) parameters, and range-relevant 3-D location parameters. Using this property we can estimate range-independent 2-D DOAs by using the RARE algorithm. Once the 2-D DOAs are available, range estimation can be obtained for each source by defining the 1-D MUSIC spectrum. Despite its low computational complexity, the proposed algorithm can provide an estimation performance almost comparable to that of the 3-D MUSIC benchmark estimator.

Joint Localization and Velocity Estimation for Pulse Radar in the Near-field Environments

  • Nakyung Lee;Hyunwoo Park;Daesung Park;Bukeun Byeon;Sunwoo Kim
    • Journal of Positioning, Navigation, and Timing
    • /
    • 제12권3호
    • /
    • pp.315-321
    • /
    • 2023
  • In this paper, we propose an algorithm that jointly estimates the location and velocity of a near-field moving target in a pulse radar system. The proposed algorithm estimates the location and velocity corresponding to the outcome of orthogonal matching pursuit (OMP) in a 4-dimensional (4D) location-velocity space. To address the high computational complexity of 4D parameter joint estimation, we propose an algorithm that iteratively estimates the target's 2D location and velocity sequentially. Through simulations, we analyze the estimation performance and verify the computational efficiency of the proposed algorithm.

딥러닝을 이용한 사용자 구분 및 위치추적 알고리즘 (User classification and location tracking algorithm using deep learning)

  • 박정탁;이솔;박병서;서영호
    • 한국정보통신학회:학술대회논문집
    • /
    • 한국정보통신학회 2022년도 춘계학술대회
    • /
    • pp.78-79
    • /
    • 2022
  • 본 논문에서는 RGB-D 카메라를 이용하여 획득한 다수 사용자의 정규화된 스켈레톤의 신체 비율 분석을 통해 각 사용자의 구분 및 위치를 추적하는 기법을 제안한다. 이를 위해 3D 포인트 클라우드로부터 각 사용자의 3D 스켈레톤을 추출한 뒤 신체 비율 정보를 저장한다. 이후 저장된 신체 비율 정보를 전체 프레임에서 출력된 신체 비율 데이터와 유사도를 비교하여 전체 영상에서의 사용자 구분 및 위치추적 알고리즘을 제안한다.

  • PDF

Four Anchor Sensor Nodes Based Localization Algorithm over Three-Dimensional Space

  • Seo, Hwajeong;Kim, Howon
    • Journal of information and communication convergence engineering
    • /
    • 제10권4호
    • /
    • pp.349-358
    • /
    • 2012
  • Over a wireless sensor network (WSN), accurate localization of sensor nodes is an important factor in enhancing the association between location information and sensory data. There are many research works on the development of a localization algorithm over three-dimensional (3D) space. Recently, the complexity-reduced 3D trilateration localization approach (COLA), simplifying the 3D computational overhead to 2D trilateration, was proposed. The method provides proper accuracy of location, but it has a high computational cost. Considering practical applications over resource constrained devices, it is necessary to strike a balance between accuracy and computational cost. In this paper, we present a novel 3D localization method based on the received signal strength indicator (RSSI) values of four anchor nodes, which are deployed in the initial setup process. This method provides accurate location estimation results with a reduced computational cost and a smaller number of anchor nodes.

3D Mesh Model Exterior Salient Part Segmentation Using Prominent Feature Points and Marching Plane

  • Hong, Yiyu;Kim, Jongweon
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • 제13권3호
    • /
    • pp.1418-1433
    • /
    • 2019
  • In computer graphics, 3D mesh segmentation is a challenging research field. This paper presents a 3D mesh model segmentation algorithm that focuses on removing exterior salient parts from the original 3D mesh model based on prominent feature points and marching plane. To begin with, the proposed approach uses multi-dimensional scaling to extract prominent feature points that reside on the tips of each exterior salient part of a given mesh. Subsequently, a set of planes intersect the 3D mesh; one is the marching plane, which start marching from prominent feature points. Through the marching process, local cross sections between marching plane and 3D mesh are extracted, subsequently, its corresponding area are calculated to represent local volumes of the 3D mesh model. As the boundary region of an exterior salient part generally lies on the location at which the local volume suddenly changes greatly, we can simply cut this location with the marching plane to separate this part from the mesh. We evaluated our algorithm on the Princeton Segmentation Benchmark, and the evaluation results show that our algorithm works well for some categories.

One-Dimensional Search Location Algorithm Based on TDOA

  • He, Yuyao;Chu, Yanli;Guo, Sanxue
    • Journal of Information Processing Systems
    • /
    • 제16권3호
    • /
    • pp.639-647
    • /
    • 2020
  • In the vibration target localization algorithms based on time difference of arrival (TDOA), Fang algorithm is often used in practice because of its simple calculation. However, when the delay estimation error is large, the localization equation of Fang algorithm has no solution. In order to solve this problem, one dimensional search location algorithm based on TDOA is proposed in this paper. The concept of search is introduced in the algorithm. The distance d1 between any single sensor and the vibration target is considered as a search variable. The vibration target location is searched by changing the value of d1 in the two-dimensional plane. The experiment results show that the proposed algorithm is superior to traditional methods in localization accuracy.

얼굴 2D 이미지의 3D 모델 변환 알고리즘 (An Algorithim for Converting 2D Face Image into 3D Model)

  • 최태준;이희만
    • 한국컴퓨터정보학회논문지
    • /
    • 제20권4호
    • /
    • pp.41-48
    • /
    • 2015
  • 최근 3D 프린터의 보급과 함께 3D 모델에 대한 수요가 급증하고 있다. 그러나 3D 모델의 생성은 숙달된 전문가가 전문 소프트웨어를 이용하여 작성하여야 한다. 본 연구는 한 장의 2차원 정면 얼굴사진으로 부터 3D 모델링하는 방법에 대한 것으로 일반인들도 쉽게 3D모델을 생성할 수 있도록 한다. 사진으로부터 배경과 전경을 분리하고 분리한 전경 영역에 일정간격으로 2차원 상에 버텍스를 배치하고 배치한 버텍스 위치를 이미지의 계조 값과 눈썹과 코 등의 특성을 고려하여 버텍스를 3차원으로 확장한다. 전경과 배경을 분리하는 방법으로 에지정보를 사용하였으며 눈과 코의 위치를 찾기 위하여 Haar-like feature를 이용하는 AdaBoost 알고리즘을 사용하였다. 알고리즘으로 생성한 3D 모델은 수작업에 의한 후처리가 필요하지만 3D 프린터를 위한 콘텐츠 제공에 매우 유용하게 활용될 것이다.

Personalized Recommendation Algorithm of Interior Design Style Based on Local Social Network

  • Guohui Fan;Chen Guo
    • Journal of Information Processing Systems
    • /
    • 제19권5호
    • /
    • pp.576-589
    • /
    • 2023
  • To upgrade home style recommendations and user satisfaction, this paper proposes a personalized and optimized recommendation algorithm for interior design style based on local social network, which includes data acquisition by three-dimensional (3D) model, home-style feature definition, and style association mining. Through the analysis of user behaviors, the user interest model is established accordingly. Combined with the location-based social network of association rule mining algorithm, the association analysis of the 3D model dataset of interior design style is carried out, so as to get relevant home-style recommendations. The experimental results show that the proposed algorithm can complete effective analysis of 3D interior home style with the recommendation accuracy of 82% and the recommendation time of 1.1 minutes, which indicates excellent application effect.

Enhancing Location Estimation and Reducing Computation using Adaptive Zone Based K-NNSS Algorithm

  • Song, Sung-Hak;Lee, Chang-Hoon;Park, Ju-Hyun;Koo, Kyo-Jun;Kim, Jong-Kook;Park, Jong-Sun
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • 제3권1호
    • /
    • pp.119-133
    • /
    • 2009
  • The purpose of this research is to accurately estimate the location of a device using the received signal strength indicator (RSSI) of IEEE 802.11 WLAN for location tracking in indoor environments. For the location estimation method, we adopted the calibration model. By applying the Adaptive Zone Based K-NNSS (AZ-NNSS) algorithm, which considers the velocity of devices, this paper presents a 9% improvement of accuracy compared to the existing K-NNSS-based research, with 37% of the K-NNSS computation load. The accuracy is further enhanced by using a Kalman filter; the improvement was about 24%. This research also shows the level of accuracy that can be achieved by replacing a subset of the calibration data with values computed by a numerical equation, and suggests a reasonable number of calibration points. In addition, we use both the mean error distance (MED) and hit ratio to evaluate the accuracy of location estimation, while avoiding a biased comparison.

  • PDF