淡江大學機構典藏:Item 987654321/104514
English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 62822/95882 (66%)
造訪人次 : 4013623      線上人數 : 888
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋
    請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/104514


    題名: Detection of Moving Objects in Image Plane for Robot Navigation using Monocular Vision
    其他題名: 應用影像平面中偵測移動物體之方法於機器人單眼視覺式巡航
    作者: Wang, Yin-Tien;Sun, Chung-Hsun;Chiou, Ming-Jang
    貢獻者: 淡江大學機械與機電工程學系
    關鍵詞: simultaneous localization;and mapping (SLAM);moving object detection (MOD);moving object tracking (MOT);speeded-up robust features (SURF);monocular vision
    日期: 2012-02-14
    上傳時間: 2016-01-06 11:00:43 (UTC+8)
    摘要: This article presents an algorithm for moving object detection (MOD) in robot visual simultaneous localization and mapping (SLAM). This MOD algorithm is designed based on the defining epipolar constraint for the corresponding feature points on image plane. An essential matrix obtained using the state estimator is utilized to represent the epipolar constraint. Meanwhile, the method of speeded-up robust feature (SURF) is employed in the algorithm to provide a robust detection for image features as well as a better description of landmarks and of moving objects in visual SLAM system. Experiments are carried out on a hand-held monocular camera to verify the performances of the proposed algorithm. The results show that the integration of MOD and SURF is efficient for robot navigating in dynamic environments.
    關聯: EURASIP Journal on Advances in Signal Processing 29
    DOI: 10.1186/1687-6180-2012-29
    顯示於類別:[人工智慧學系] 期刊論文

    文件中的檔案:

    檔案 描述 大小格式瀏覽次數
    index.html0KbHTML195檢視/開啟
    Wang2012_Article_DetectionOfMovingObjectsInImag.pdf6010KbAdobe PDF1檢視/開啟

    在機構典藏中所有的資料項目都受到原著作權保護.

    TAIR相關文章

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