# 臺灣博碩士論文加值系統

(3.236.68.118) 您好！臺灣時間：2021/07/31 19:57

:::

### 詳目顯示

:

• 被引用:0
• 點閱:145
• 評分:
• 下載:0
• 書目收藏:0
 利用深度相機取得的三維場景的去模糊化在電腦視覺領域中是一個新穎的題目。動態模糊(motion blur)發生在許多基於結構光(structured light)的三維相機中。我們分析了基於結構光的三維相機產生動態模糊的原因，並設計了一個新穎的方法在三維場景中去模糊化。我們利用物體的模型去取代三維場景中有動態模糊的部分。因為我們處理連續的三維影像，因此我們可以在物體還沒產生動態模糊時建出物體的模型。我們的去模糊演算法分為兩個部分：動態模糊偵測以及動態模糊去模糊化。在動態模糊偵測部分，我們依物體的速度來辦定是否產生動態模糊。在動態模糊去模糊化部分，我們先判斷動態模糊的種類，並應用跌代最近點演算法(iterative closest point algorithm)針對不同種類的動態模糊來做不同的處理。我們對三組真實數據(real data)做實驗，成功得到了去模糊化的結果。
 Deblurring of 3D scenes captured by 3D sensors is a novel topic in computer vision. Motion blur occurs in a number of 3D sensors based on structured light techniques. We analyze the causes of motion blur captured by structured light depth cameras and design a novel algorithm using the speed cue and object models to deblur a 3D scene. The main idea is using the 3D model of an object to replace the blurry object in the scene. Because we aim to deal with consecutive 3D frame sequences, ie 3D videos, an object model can be built in the frame where the object is not blurry yet. Our deblurring method can be divided into two parts: motion blur detection and motion blur removal. For the motion blur detection part, we use the speed cue to detect where the motion blur is. For the motion blur removal part, first we judge the type of the motion blur, and then we apply the iterative closest point (ICP) algorithm in different ways according to the motion blur type. The proposed method is evaluated in real world cases and successfully accomplishes motion blur detection and blur removal.
 CHAPTER 1. Introduction 1CHAPTER 2. RelatedWork 3CHAPTER 3. Motion Blur Detection 53.1. The Foundation of Structured Light 53.2. Causes of Motion Blur of Structured Light Depth Cameras 73.3. The Difference between Motion Blur in 2D Images and 3D Piont Clouds 73.4. Our Blur Detection Method 12CHAPTER 4. Deblurring 144.1. Building Object Model 144.2. Judge the Type of Motion Blur 144.3. Find the Correct Object Model Pose 17CHAPTER 5. Experiment and Discussion 195.1. Experiment Setup 195.2. Experiment Results and Discussion 19CHAPTER 6. Conclusion and Future Work 25BIBLIOGRAPHY 27
 Arieli, Y., Freedman, B., Machline, M., & Shpunt, A. (2012). Depth mapping using projectedpatterns. US Patent 8,150,142.Bascle, B., Blake, A., & Zisserman, A. (1996). Motion deblurring and super-resolution froman image sequence. In Computer VisionECCV’96 (pp. 571–582). Springer.Cho, S. & Lee, S. (2009). Fast motion deblurring. In ACM Transactions on Graphics (TOG),volume 28, (pp. 145).Girod, B. & Scherock, S. (1990). Depth from defocus of structured light. In 1989 Advancesin Intelligent Robotics Systems Conference, (pp. 209–215).Khoshelham, K. (2011). Accuracy analysis of kinect depth data. In ISPRS workshop laserscanning, volume 38, (pp. W12).Kim, T. H., Ahn, B., & Lee, K. M. (2013). Dynamic scene deblurring. In 2013 IEEE InternationalConference on Computer Vision (ICCV), (pp. 3160–3167).Kim, T. H. & Lee, K. M. (2014). Segmentation-free dynamic scene deblurring. In 2014 IEEEConference on Computer Vision and Pattern Recognition (CVPR), (pp. 2766–2773).Liu, R., Li, Z., & Jia, J. (2008). Image partial blur detection and classification. In IEEEConference on Computer Vision and Pattern Recognition, 2008. CVPR 2008, (pp. 1–8).Nayar, S. & Ben-Ezra, M. (2004). Motion-based motion deblurring. IEEE Transactions onPattern Analysis and Machine Intelligence, 26(6), 689–698.Ringaby, E. & Forss´en, P.-E. (2011). Scan rectification for structured light range sensorswith rolling shutters. In 2011 IEEE International Conference on Computer Vision (ICCV),(pp. 1575–1582).Scharstein, D. & Szeliski, R. (2003). High-accuracy stereo depth maps using structuredlight. In 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition,2003. Proceedings, volume 1, (pp. I–195).
 國圖紙本論文
 推文當script無法執行時可按︰推文 網路書籤當script無法執行時可按︰網路書籤 推薦當script無法執行時可按︰推薦 評分當script無法執行時可按︰評分 引用網址當script無法執行時可按︰引用網址 轉寄當script無法執行時可按︰轉寄

 無相關論文

 1 23. 陳錦烽，“我國股票上市公司之實證研究--衍生性金融商品的使用及財務報導”，會計研究月刊，第126 期。

 無相關點閱論文

 簡易查詢 | 進階查詢 | 熱門排行 | 我的研究室