| 課程大綱 Syllabus |
學生學習目標
Learning Objectives |
單元學習活動
Learning Activities |
學習成效評量
Evaluation |
備註
Notes |
序
No. | 單元主題
Unit topic |
內容綱要
Content summary |
| 1 | Introduction |
Computer Vision and Applications |
了解為何要學電腦視覺 |
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| 2 | Camera Model and Image Representation |
1. 2D image from projection of a 3D scene
2. Imaging formation
3. Pin-hole camera
4. Video cameras
5. Lab: OpenCV 影像儲存 |
影像之基本處理 |
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| 3 | Filtering and Enhancing Images |
1. Gray level transformations
2. Histogram processing
3. Enhancement using arithmetic operations
4. Spatial filtering
5. Lab: 美化影像 |
學會使用OpenCV做基本影像處理 |
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| 4 | Binary Image Processing |
1. Pixels and neighborhood
2. Applying masks to images
3. Counting the object in an image
4. Connected components labeling
5. Binary image morphology
6. Region properties
7. Region adjacency graphs
8. Thresholding gray-scale images
9. Lab: Connected Component |
學會抽取特徵 |
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| 5 | Case study - OCR |
1. Handwritten OCR systems
2. CIL - Greek Handwritten Character Database
3. Proposed OCR Methodology
4. Experimental Results
5. Experiments on Historical Documents
6. Lab: OCR |
學會寫程式進行文字辨識 |
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| 6 | Image Segmentation |
1. Clustering
2. K-means
3. Region Growing
4. Lab: Segmentation |
Ideally, partition an image into regions corresponding to real world objects |
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| 7 | Case study - Multi-Focus Images Fusion |
1. Region-based image fusion methods
2. Multifocus images fusion by average
3. Intermediate fused image is segmented
4. Source images are segmented according to the segmenting result
5. Segmented regions of the source images are fused
6. Lab: Multi-Focus Images Fusion |
Multifocus image fusion using region segmentation and spatial frequency |
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| 8 | Case study –High Dynamic Range Image |
1. 使用HDR顯示設備
2. 透過不同曝光程度顯示HDR影像
3. 色調映射(Tone mapping)
4. Lab: HDRI Fusion |
學會製作HDRI |
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| 9 | 期中考 |
考試 |
通過測試 |
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| 10 | Case study - Motion from 2D Image Sequences |
1. 2-D motion vs. optical flow
2. Motion representation
3. Motion estimation criterion
4. Optimization methods
5. Gradient descent methods
6. Lab: Optical Flow |
運動偵測 |
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| 11 | Intelligent Video Surveillance |
1. 產品需求及產業趨勢
2. 應用情境及技術挑戰
3. 工研院研發成果暨產業應用 |
了解產業需求 |
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| 12 | Case study - Behavior Analysis |
1. Motion segmentation
2. Morphological operation
3. Object classification
4. Tracking
5. Lab: Tracking |
學會監控技術 |
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| 13 | Object Matching - SIFT |
1. Scale Space and Difference of Gaussian
2. Key point Localization
3. Orientation Assignment
4. Descriptor Building
5. Application
6. Lab: Object Recognition |
學會利用SIFT作物體比對 |
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| 14 | Pattern Recognition Concept |
1. Common model for classification
2. Precision vs. recall
3. Feature vector representation
4. Implementing the classifier
5. Structural techniques
6. The confusion matrix
7. Decision trees
8. Matching by relations
9. Lab: Neural Network |
了解圖形識別技術 |
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| 15 | Face Detection and Recognition |
1. Face feature
2. Integral image
3. Ada-boost
4. Face detection
5. Lab: Face Detection |
學會寫程式偵測人臉 |
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| 16 | Gesture Recognition |
1. 影像處理方法
2. 影像金字塔
3. 人臉偵測
4. 數位變焦
5. 適應性膚色偵測
6. 動態歷史影像
7. Lab: Hand Gesture Recognition |
學會偵測手勢 |
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| 17 | Special Topic |
自選研究題目 |
找論文，自行研究 |
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| 18 | 期末考 |
考試 |
通過測試 |
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