投影機相機(projector camera)系統近年相當流行，主要原因是它能夠靈活地展示影像，使用戶有更大的自由度作出操作。手提式投影機的技術在過往幾年急速發展、漸見成熟，知名的家用電子産品生産廠閱始推出内置迷你投影機的手機和攝影機。另一方面手機的運算能力正急劇地提升，它們多都配置不同種類且功能强大的周邊設備。 / 本論文提出並討論一種基於現場可编程邏輯閘陣列(Field Programmable Gate Array, FPGA),並適用於嵌入式系统的特殊處理器。該特殊處理器專門處理來自相機的資料串流，透過一系列的象素圖像處理運算如圖像梯度和高斯模糊，去找出相中物件的邊緣，藉此分擔微處器在運算上的負擔。實驗結果明這特殊處理器可實現於低端的FPGA上並和普遍的微處器一起運作。 / 本論文第二個探討的主題是一個利用多模卡爾曼濾波器(Multiple Model Kalman Filter)的直線追踪器，並利用多個直線追踪器去作投影面板的追踪。利用卡爾曼濾波器只需要很低的運算能力的優點,我們的直線追踪器在嵌入式系统實測時能達到每秒200幀的速度。多模卡爾曼濾波器在實驗中有滿意的成績並較單卡爾曼濾波器和擴展卡爾曼濾波器優異。 / Projector-camera (ProCam in short) systems are getting very popular since the user can change the display area dynamically and enjoy more freedom in handling the device. In recent years, the mobile projector technology is becoming mature and manufacturers are shipping mobile phones and digital cameras with projectors. On the other hand, the computation power of a cell phone had dramatically increased and the cell phones are accompanied with large number of powerful peripherals. / In this thesis, the possibility of making an embedded Projector-camera (ProCam) system is investigated. A ProCam system is developed by our research group previously and designed for desktop Personal Computers(PCs). The system uses computer vision techniques to detect a white cardboard as the projection screen and uses particle filter to trace the screen in subsequent frames. The system demands a large computation power, unfortunately the power of low cost embedded system is still not powerful enough to implement the ProCam system.Therefore, specially designed hardware and computationally efficient algorithm are required in order to implement the ProCam system on an embedded system. / An FPGA based special processor to share the workload of the microcontroller in the embedded system is proposed and tested. This special processor will take the data stream of the camera as the inputs and apply pixel-wise image operators such as image gradient and Gaussian blur in order to extract the edge pixels. As a result, the workload of the microcontroller in the embedded system is reduced. The experiments show that the design can be implement on a low-end FPGA with a simple microcontroller. / A line tracker using Multiple Model Kalman lter is also proposed in this thesis. The aim of this tracker is to reduce the time on tracking the board. Benet from the low computation requirement of Kalman filter, the proposed line tracker can run in 200 fps on our testing embedded system. The experiments also show that the robustness of the Multiple Model Kalman filter is satisfactory and it outperforms the line trackers using single Kalman filter or extended Kalman filter alone. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Fung, Hung Kwan. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 115-124). / Abstracts also in Chinese. / Abstract --- p.ii / Acknowledgement --- p.v / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivation and Objective --- p.1 / Chapter 1.2 --- Contributions --- p.3 / Chapter 1.3 --- Thesis Organization --- p.5 / Chapter 2 --- Background --- p.7 / Chapter 2.1 --- Introduction --- p.7 / Chapter 2.2 --- Projector-Camera System --- p.8 / Chapter 2.2.1 --- Static Projector-Screen --- p.9 / Chapter 2.2.2 --- Dynamic Projector-Screen --- p.13 / Chapter 2.3 --- Embedded Vision --- p.15 / Chapter 2.4 --- Summary --- p.25 / Chapter 3 --- System Overview --- p.26 / Chapter 3.1 --- System Design --- p.26 / Chapter 3.2 --- Our Approach --- p.28 / Chapter 3.2.1 --- Projector-camera system --- p.28 / Chapter 3.2.2 --- Smart Camera --- p.31 / Chapter 3.2.3 --- Quadrangle Detection and Tracking Module --- p.32 / Chapter 3.2.4 --- Projection Module --- p.32 / Chapter 3.3 --- Extension --- p.33 / Chapter 4 --- Smart Camera --- p.34 / Chapter 4.1 --- Introduction --- p.34 / Chapter 4.2 --- Hardware Overview --- p.35 / Chapter 4.3 --- Image Acquisition --- p.40 / Chapter 4.4 --- Image Processing --- p.42 / Chapter 4.4.1 --- RGB-to-Gray Conversion Module . --- p.44 / Chapter 4.4.2 --- Image Smoothing Module --- p.45 / Chapter 4.4.3 --- Image Gradient Module --- p.49 / Chapter 4.4.4 --- Non-maximum Suppression and Hysteresis Thresholding --- p.53 / Chapter 4.5 --- Summary --- p.55 / Chapter 5 --- Quadrangle Detection and Tracking --- p.57 / Chapter 5.1 --- Introduction --- p.57 / Chapter 5.2 --- Line Feature Extraction --- p.61 / Chapter 5.3 --- Automatic Quadrangle Detection --- p.62 / Chapter 5.4 --- Real-time Quadrangle Tracking --- p.68 / Chapter 5.4.1 --- Line Tracker --- p.69 / Chapter 5.5 --- Tracking Lose Strategy --- p.76 / Chapter 5.6 --- Recover from Tracking Failure --- p.77 / Chapter 5.7 --- Summary --- p.77 / Chapter 6 --- Implementation and Experiment Result --- p.79 / Chapter 6.1 --- Introduction --- p.79 / Chapter 6.2 --- Smart Camera --- p.79 / Chapter 6.3 --- Line Tracking --- p.87 / Chapter 7 --- Limitation and Discussion --- p.101 / Chapter 7.1 --- Introduction --- p.101 / Chapter 7.2 --- Limitation --- p.101 / Chapter 7.3 --- Summary --- p.105 / Chapter 8 --- Application --- p.107 / Chapter 8.1 --- Introduction --- p.107 / Chapter 8.2 --- Portable Projector-Camera System --- p.107 / Chapter 8.3 --- Summary --- p.110 / Chapter 9 --- Conclusion --- p.112 / Bibliography --- p.115
| Identifer | oai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_328487 |
| Date | January 2012 |
| Contributors | Fung, Hung Kwan., Chinese University of Hong Kong Graduate School. Division of Computer Science and Engineering. |
| Source Sets | The Chinese University of Hong Kong |
| Language | English, Chinese |
| Detected Language | English |
| Type | Text, bibliography |
| Format | electronic resource, electronic resource, remote, 1 online resource (xiv, 124 leaves) : ill. (some col.) |
| Rights | Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/) |
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