淡江大學機構典藏:Item 987654321/115011
English  |  正體中文  |  简体中文  |  Items with full text/Total items : 58323/91877 (63%)
Visitors : 14381244      Online Users : 113
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/115011


    Title: Efficient Model-Based Object Pose Estimation Based on Multi-Template Tracking and PnP Algorithms
    Authors: Chi-Yi Tsai;Kuang-Jui Hsu;Humaira Nisar
    Keywords: model-based pose estimation;3D pose estimation;homography decomposition;PnP problem;template tracking
    Date: 2018-08-12
    Issue Date: 2018-09-27 12:10:23 (UTC+8)
    Abstract: Three-Dimensional (3D) object pose estimation plays a crucial role in computer vision because it is an essential function in many practical applications. In this paper, we propose a real-time model-based object pose estimation algorithm, which integrates template matching and Perspective-n-Point (PnP) pose estimation methods to deal with this issue efficiently. The proposed method firstly extracts and matches keypoints of the scene image and the object reference image. Based on the matched keypoints, a two-dimensional (2D) planar transformation between the reference image and the detected object can be formulated by a homography matrix, which can initialize a template tracking algorithm efficiently. Based on the template tracking result, the correspondence between image features and control points of the Computer-Aided Design (CAD) model of the object can be determined efficiently, thus leading to a fast 3D pose tracking result. Finally, the 3D pose of the object with respect to the camera is estimated by a PnP solver based on the tracked 2D-3D correspondences, which improves the accuracy of the pose estimation. Experimental results show that the proposed method not only achieves real-time performance in tracking multiple objects, but also provides accurate pose estimation results. These advantages make the proposed method suitable for many practical applications, such as augmented reality.
    Relation: Algorithms 2018 11(8), 122
    DOI: 10.3390/a11080122
    Appears in Collections:[Graduate Institute & Department of Electrical Engineering] Journal Article

    Files in This Item:

    File Description SizeFormat
    Efficient Model-Based Object Pose Estimation Based on Multi-Template Tracking and PnP Algorithms.pdf2802KbAdobe PDF89View/Open
    index.html0KbHTML149View/Open

    All items in 機構典藏 are protected by copyright, with all rights reserved.


    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback