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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 傅楸善 | zh_TW |
| dc.contributor.advisor | Chiou-Shann Fuh | en |
| dc.contributor.author | 邵育翔 | zh_TW |
| dc.contributor.author | Yu-Hsiang Shao | en |
| dc.date.accessioned | 2023-03-19T23:20:34Z | - |
| dc.date.available | 2023-12-26 | - |
| dc.date.copyright | 2022-08-02 | - |
| dc.date.issued | 2022 | - |
| dc.date.submitted | 2002-01-01 | - |
| dc.identifier.citation | [1] L. Li, “Time-of-Flight Camera – An Introduction,” Texas Instrument Technical White Paper, 2014.
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/85650 | - |
| dc.description.abstract | iTOF (indirect Time-of-Flight)間接飛時相機是藉由偵測到光波訊號碰到物體來回的相位差進行深度預測。如：Kinect 2.0、Samsung Galaxy手機深度鏡頭都是使用相關技術。然而，iToF 相機在偵測深度的過程中非常容易被外界影響，如：光線、溫度、接收器上每一個像素所接收到的時間差等都是需要在iToF相機出廠前進行校正以確保深度精準度。此篇研究主要探討iToF系统性的錯誤：擺動(Wiggling)、固定相位模式雜訊 (Fixed Phase Pattern Noise)、溫度漂(Temperature Drift)、鏡頭校正(Lens Distortion)，四個項目進行深度鏡頭校正任務。
此篇論文會首先透過相位差計算偵測點深度，再透過傅立葉轉換找出最高與次高頻區間段，利用傅立葉反轉換回推每一像素針對擺動誤差的修正。固定相位模式雜訊為了將整體誤差降到最低，會透過不同深度計算偵測與實際深度誤差進行評估與多項式函式擬合方法找出最接近數值。此篇論文創造將四種不同深度放於一張相片進行校正，可以在最短時間內找出固定相位模式誤差的參數統計。溫度飄移在本篇論文會透過熱箱在不同溫度下的統計進行查表校正。最後在鏡頭校正部分則使用針孔相機模型與張正友校正法進行鏡頭評估。找出相機內部與外部參數，同時也計算出輻射失真、鏡頭與相機感測器之間的切向失真參數。 | zh_TW |
| dc.description.abstract | iToF, indirect Time-of-Flight, camera predicts depth by detecting the phase difference between the light-wave signal and the object, such as Kinect 2.0, and Samsung Galaxy mobile phone. However, iToF camera will easily be affected by the external environment when detecting depth, for example, sunlight temperature, time difference received by each pixel on the receiver, and so on. All need to be calibrated before leaving the factory to ensure depth accuracy. This study will mainly discuss the systematic errors of iToF: Wiggling, Fixed Phase Pattern Noise, Temperature Drift, Lens Distortion: the four main errors that affect results.
This thesis will first discuss how to calculate the depth information through different phases detected by iToF sensor, and then use Fourier transform to find the highest and second-highest frequency intervals, then use inverse Fourier transform to push back the correction of the wiggling error for each pixel. Besides, to minimize the fixed phase pattern noise, the actual depth errors are evaluated through the polynomial function fitting method. To get better results, we also focus on temperature drift by look-up table through the statistics of the thermal chamber at different temperatures. Finally, we use pinhole camera model to calibrate lens distortion. | en |
| dc.description.provenance | Made available in DSpace on 2023-03-19T23:20:34Z (GMT). No. of bitstreams: 1 U0001-0906202218241500.pdf: 7607988 bytes, checksum: 1cc2ec9e93935ec8817025f7c5249151 (MD5) Previous issue date: 2022 | en |
| dc.description.tableofcontents | CONTENTS
口試委員會審定書 i 誌謝 ii 中文摘要 iii ABSTRACT iv CONTENTS v LIST OF FIGURES viii LIST OF TABLES xii Chapter 1 Introduction 1 1.1 Introduction for 3D camera 1 1.2 Introduction for ToF Camera 3 1.3 The Advantage of ToF Camera 5 1.4 The Disadvantage of ToF Camera 6 1.4.1 General Shortcoming 6 1.4.2 Extrinsic Influence 7 1.4.3 Systematic Error 9 1.5 Thesis Organization 9 Chapter 2 Related Works 11 2.1 History of 3D camera 11 2.2 3D View Implemented by Kinect v2 15 2.3 Difference between iToF Camera and dToF Camera 19 2.4 iToF Camera Calibration 22 Chapter 3 Background 26 3.1 iToF Camera Depth Calculation 26 3.2 Four Different Systematic Errors for iToF Camera 27 3.2.1 Temperature Drift 27 3.2.2 Wiggling Error 28 3.2.3 Lens Distortion 29 3.2.4 FPPN Error 31 Chapter 4 Methodology 32 4.1 Overview 32 4.2 Data Collection 33 4.3 ShaoCalibrate 36 4.3.1 Temperature Drift Calibration 36 4.3.2 Wiggling Calibration 38 4.3.3 Lens Distortion Calibration 43 4.3.4 FPPN Calibration 46 Chapter 5 Experimental Results 49 5.1 Experimental Setting 49 5.2 Lens Distortion and Camera Calibration Result 50 5.3 FPPN Result 53 5.4 Depth Estimation after ShaoCalibrate 55 Chapter 6 Conclusion and Future Works 62 References 63 | - |
| dc.language.iso | en | - |
| dc.subject | 邵校正 | zh_TW |
| dc.subject | 間接飛時相機校正 | zh_TW |
| dc.subject | 系統性誤差校正 | zh_TW |
| dc.subject | 快速固定相位模式雜訊校正 | zh_TW |
| dc.subject | 間接飛時相機校正 | zh_TW |
| dc.subject | 邵校正 | zh_TW |
| dc.subject | 系統性誤差校正 | zh_TW |
| dc.subject | 快速固定相位模式雜訊校正 | zh_TW |
| dc.subject | iToF Camera Calibration | en |
| dc.subject | ShaoCalibrate | en |
| dc.subject | iToF Camera Calibration | en |
| dc.subject | ShaoCalibrate | en |
| dc.subject | Systematic Error Correction | en |
| dc.subject | Systematic Error Correction | en |
| dc.title | 邵校正: 三維飛時相機深度校正 | zh_TW |
| dc.title | ShaoCalibrate: 3D Time-of-Flight Camera Depth Calibration | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 110-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 賴志宏;巫宗昇;沈立健 | zh_TW |
| dc.contributor.oralexamcommittee | Jr-Hung Lai;Tzung-Sheng Wu;Li-Jian Shen | en |
| dc.subject.keyword | 間接飛時相機校正,邵校正,系統性誤差校正,快速固定相位模式雜訊校正, | zh_TW |
| dc.subject.keyword | iToF Camera Calibration,ShaoCalibrate,Systematic Error Correction, | en |
| dc.relation.page | 67 | - |
| dc.identifier.doi | 10.6342/NTU202200899 | - |
| dc.rights.note | 同意授權(全球公開) | - |
| dc.date.accepted | 2022-06-27 | - |
| dc.contributor.author-college | 電機資訊學院 | - |
| dc.contributor.author-dept | 生醫電子與資訊學研究所 | - |
| dc.date.embargo-lift | 2027-06-21 | - |
| 顯示於系所單位： | 生醫電子與資訊學研究所 | |
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|---|---|---|---|
| ntu-110-2.pdf 此日期後於網路公開 2027-06-21 | 7.43 MB | Adobe PDF |
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