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研究生:晋萱
研究生(外文):Hsuan Chin
論文名稱:應用室內定位於物品搜尋之研究
論文名稱(外文):A Study on Object Locating via Indoor Positioning
指導教授:楊傳凱
指導教授(外文):Chuan-Kai Yang
口試委員:林伯慎孫沛立
口試委員(外文):Bor-Shen LinPei-Li Sun
口試日期:2019-6-25
學位類別:碩士
校院名稱:國立臺灣科技大學
系所名稱:資訊管理系
學門:電算機學門
學類:電算機一般學類
論文種類:學術論文
論文出版年:2019
畢業學年度:107
語文別:中文
論文頁數:53
中文關鍵詞:地磁室內定位地磁室內導航物體辨識洪水填滿演算法
外文關鍵詞:Geomagnetic Indoor PositioningGeomagnetic Indoor NavigationObject RecognitionFlood Filling Algorithm
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日常生活中,我們或許都有找不到某個物品的經驗,特別是在家中,因此本論文提出了一個能記錄室內物品擺放位置的行動app,透過物體辨識來識別相機畫面中出現的物品,並同時運用地磁室內定位以得知當前所在的室內座標,並將物品資訊記錄於資料庫中,當下次要尋找該物品時,運用地磁室內導航至該物品位置,讓尋找物品變得更容易。
為了讓使用者更清楚所在位置,本論文也提出行徑路線顯示之方法,結合地磁室內定位數據及洪水填滿演算法,透過邊走邊畫的方式呈現使用者的行徑路線,並建構出簡易的室內平面圖。
In our daily life, we may have experience on try finding an object, especially at home. This paper proposes a mobile app that records the location of indoor objects, and identifies objects appearing in the camera through object recognition. At the same time, the geomagnetic indoor positioning is used to obtain the current indoor coordinates, and the object information is recorded in the database. When the object is to be searched later on, the geomagnetic information is used to navigate to the object location, so that it is easier to find it.
In order to make the user more aware of the location, this paper also proposes a method on the route display, combined with the geomagnetic indoor positioning data and the flood filling algorithm, so that we can present the user's path while walking, and construct a simple indoor floor plan.
中文摘要.................................................................. III
英文摘要.................................................................. IV
誌謝 ...................................................................... V
目 錄 ..................................................................... VI
圖目錄 .................................................................... VIII
表目錄 .................................................................... XI
第一章 緒論 .............................................................. 1
1.1 研究動機與目的 ............................................................ 1
1.2 論文架構 .................................................................... 1
第二章 文獻探討 ......................................................... 3
2.1 iBeacon .................................................................... 3
2.2 地磁定位 ............................................................... 5
2.3 藍芽.................................................................. 6
2.4 物體辨識 ............................................................... 7
第三章 演算法設計與系統實作............................................ 10
3.1 系統流程 .................................................................... 10
3.2 行徑路線顯示(Route Display)............................................. 11
3.2.1 地磁室內定位 . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
3.2.2 邊走邊畫 . . . . . . . . . . . . . . . . . . . . . . . 13
3.2.3 洪水填滿演算法 . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
3.3 物品資訊記錄(Item Information Record)................................................. 16
3.3.1 物體辨識使用工具 . . . . . . . . . . . . . . . . . . . . . . . . 16
3.3.2 Tensorflow訓練過程 . . . . . . . . . . . . . . . . . . . . . . . . 17
3.3.3 物體辨識 . . . . . . . . . . . . . . . . . . . . . . . . 21
3.3.4 物體距離計算 . . . . . . . . . . . . . . . . . . . . . . . . 21
3.3.5 物體定位 . . . . . . . . . . . . . . . . . . . . . . . . 22
3.4 語音檢索 (Voice Retrieval) ................................... 23
3.5 地磁室內導航(Geomagnetic Indoor Navigation)............................................. 24
第四章 結果展示與評估................................................... 26
4.1 系統環境 .................................................................... 26
4.2 系統流程圖.......................................................... 27
4.3 物品記錄 .................................................................... 28
4.3.1 介面說明 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
4.3.2 結果展示 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
4.4 物品尋找 .................................................................... 35
第五章 系統實驗 ......................................................... 38
第六章 結論與未來展望................................................... 39
參考文獻.................................................................. 40
[1] IndoorAtlas. https://www.indooratlas.com/.
[2] Mapping. https://docs.indooratlas.com/app/.
[3] Flood Fill Algorithm.
http://melonteam.com/posts/tu_xiang_chu_li_zhi_man_shui_tian_chong_suan_fa_flood_fill_algorithm_/.
[4] Google Cloud Vision API.
https://cloud.google.com/vision/?hl=zh-tw.
[5] Clarifai API. https://clarifai.com/.
[6] Tensorflow Mobile.
https://github.com/tensorflow/tensorflow/tree/master/tensorflow/examples/android.
[7] Tensorflow Model. https://github.com/tensorflow/models.
[8] Tensorflow Object Detection Model.
https://github.com/EdjeElectronics/TensorFlow-Object-Detection-API-Tutorial-Train-Multiple-Objects-Windows-10.
[9] Tensorflow Detection Model Zoo.
https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md.
[10] labelimg. https://github.com/tzutalin/labelImg#installation.
[11] Feriştah Dalkılıç, Emine Arıkan, Aslıhan Gürkan, Umut Can Çabuk, “An Analysis of the Positioning Accuracy of iBeacon Technology in Indoor Environments”, International Conference on Computer Science and Engineering (UBMK), 2017.
[12] Noah Pritt, “Indoor Navigation with use of Geomagnetic Anomalies”, IEEE Geoscience and Remote Sensing Symposium, 2014.
[13] Adam Satan, “Bluetooth-based Indoor Navigation Mobile System”, 19th International Carpathian Control Conference (ICCC), 2018.
[14] Sadi Rafsan, Safayet Arefin, A. H. M. Mirza Rashedul Hasan, and Mohammed Moshiul Hoque, “Design a Human-Robot Interaction Framework to Detect Household Objects”, International Conference on Informatics, Electronics and Vision (ICIEV), 2016.
[15] Sana Liaquat and Umar S. Khan, Ata-ur-Rehman, “Object Detection and Depth Estimation of Real World Objects using Single Camera”, Fourth International Conference on Aerospace Science and Engineering (ICASE), 2015.
[16] Yasir M Mustafah, Rahizall Noor, Hasbullah Hasbi, Amelia Wong Azma, “Stereo Vision Images Processing for Real-time Object Distance and Size Measurements”, International Conference on Computer and Communication Engineering (ICCCE), 2012.
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