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研究生:簡睿成
研究生(外文):Jui-Cheng Chien
論文名稱:以物體為基礎的影片壓縮技術之研究
論文名稱(外文):A Study on Object-Based Video Compression
指導教授:陳玲慧陳玲慧引用關係
指導教授(外文):Ling-Hwei Chen
學位類別:碩士
校院名稱:國立交通大學
系所名稱:資訊科學系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2002
畢業學年度:90
語文別:英文
論文頁數:49
中文關鍵詞:物體切割以物體為基礎的影片壓縮位移偵測
外文關鍵詞:object segmentationobject-based video compressionmotion estimation
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以物體為基礎的影片壓縮方法是現在很熱門的題目,也是一個影片壓縮很重要的發展方向。藉由將物體由背景中擷取出來,並且針對不同的物體作個別的處理,使得影片壓縮更有效率和彈性。在這篇論文中,我們首先提出一個將剛性(不形變)物體由背景中切割出來的方法,這個方法主要是藉由分析兩張連續影像內容的移動資訊來達成;接著我們提出一個以物體為基礎的影片壓縮方法,利用前一個方法先切割出影片中的物體,我們只需要紀錄物體和背景在之後的畫面中如何移動,以及紀錄一些因為攝影機移動或物體移動而新出現的背景區域像素即可,如此一來,就可以相當有效率地壓縮影片。

Object-based video compression is a hot topic. This kind of techniques separates objects from the background and encodes objects individually. In this thesis, we will propose an object segmentation method and an object-based video compression method. Both methods are fully automatic. The object segmentation approach provides the ability to extract rigid objects from two consecutive frames with or without background motion. The main idea is to analyze the motion information between two frames. Then the result of object segmentation could be used in the object-based video compression method. The object in each frame could be considered the same as the first extracted one. So we only need to record the motions of background and the object in each frame. And the new appeared background area also needs to be recorded. Thus, only a little information is needed to reconstruct the original video.

CHAPTER 1 INTRODUCTION ................................... 1
1-1. Motivation ................................. 1
1-2. Previous works ............................. 2
1-3. Proposed method ............................ 6
CHAPTER 2 PRELIMINARY .................................... 8
2-1. The n-step search algorithm ................ 8
2-2. Hough transform ........................... 11
2-3. Chain codes ............................... 14
2-4. Huffman coding ............................ 16
CHAPTER 3 RIGID OBJECT SEGMENTATION ..................... 20
3-1. Overview of the proposed rigid object segmentation method ..................................... 20
3-2. Block motion estimation ................... 20
3-3. Rigid object extraction ................... 22
3-4. Segmented result refinement ............... 28
CHAPTER 4 OBJECT-BASED VIDEOO COMPRESSION ............... 33
4-1. Overview of the proposed object-based video compression method ...................................... 33
4-2. Object model construction ................. 34
4-3. Motion estimation for objects and background .............................................. 35
4-4. Residual area coding ...................... 36
4-5. Decompression ............................. 39
CHAPTER 5 EXPERIMENTAL RESULTS .......................... 41
5-1. Experimental results of the rigid object segmentation approach ................................... 41
5-2. Experimental results of object-based video compression ............................................. 43
CHAPTER 6 CONCLUSIONS ................................... 49
REFERENCES .............................................. 51
LIST OF TABLES
Table 2-1 An example of codebook ........................ 17
Table 2-2 An example of Huffman coding table ............ 18
Table 5-1. Compression rate table ....................... 44
LIST OF FIGURES
Fig. 2.1. Definition of the search windows ............... 9
Fig. 2.2 An example of the three-step search algorithm with resulting motion vector (6, -4) ......................... 11
Fig. 2.3 An example to explain the idea of Hough transform ............................................... 12
(a) A line with parameters (a’, b’) passing two points A and B in the xy plane.
(b) Two corresponding lines of A and B intersecting at (a’, b’) in the parameter space.
Fig. 2.4. Quantization of the parameter plane for use in the Hough transform ......................................... 13
Fig. 2.5. Normal representation of a line ............... 14
Fig. 2.6. Chain code directions ......................... 15
(a) 4-directional chain code.
(b) 8-directional chain code.
Fig. 2.7. Two examples for chain code coding ............ 16
(a) 4-directional chain code.
(b) 8-directional chain code.
Fig. 2.8. Example of Huffman coding tree ................ 19
Fig. 3.1. The overall block diagram of the rigid object segmentation approach ................................... 20
Fig. 3.2. An example of a block motion table with origin at the center and the number in entry (i, j) standing for the number of blocks with motion vector (i, j) ..................... 22
Fig. 3.3. The blocks with motion vector (0, 0) grouped into three different connected regions marked by different colors .................................................. 23
Fig. 3.4. The bounding rectangle for those blocks with the same motion created .......................................... 24
Fig. 3.5. The distribution of different motion vectors from an object .................................................. 26
(a) A frame.
(b) The next frame of (a).
(c) The block motion table.
(d) The blocks with motion (-3,0).
(e) The blocks with motion (-2,0).
(f) The blocks with motion (0,0).
Fig. 3.6. An example of connecting split objects ........ 31
(a) The segmented result before object refinement.
(b) The difference point of comparing two consecutive frames.
(c) The result of object refinement.
Fig. 3.7. An example of eliminating background noises ... 32
Fig. 4.1. The overall block diagram of the rigid object segmentation approach ................................... 34
Fig. 4.2. An example for object model extraction on frame 131 of sequence “Coastguard” .............................. 34
(a) Segmented result.
(b) Object model extracted.
Fig. 4.3. An example of edge blocks of the segmented result in Fig. 4.2 (a) ............................................ 35
Fig. 4.4. An example to show the residual area .......... 37
(a) Original frame.
(b) The new appeared background area marked by blue color.
(c) The object edge area marked by red color.
Fig. 4.5. An example of raster scan and the first two extracted pixels .................................................. 38
Fig. 4.6. The overall block diagram of the object-based video decoder ................................................. 40
Fig. 5.1. The segmented result of “Coastguard” ........ 42
Fig. 5.2. Some noises in the segmented result of “Coastguard” at frame 3 .............................................. 42
Fig. 5.3. The segmented result of video “Car” ......... 43
(a) Frame 12.
(b) Frame 76.
Fig. 5.4. An example of compression results ............ 45
(a) The original frame 170 of video “Coastguard”.
(b) The compression result of (a) using automatic object segmentation.
(c) The compression result of (a) using manual object segmentation.
Fig. 5.5. An example of compression results ............. 46
(a) The original frame 90 of video “Car”.
(b) The compression result of (a) using automatic object segmentation.
(c) The compression result of (a) using manual object segmentation.

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[3] J. Stepan and M. Jirina, “Moving object tracking in the sequence of images acquired from non-stationary camera,” Proc. 2001 IEEE International Conference on Image Processing, Vol. 1, pp. 353-356, 2001.
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[6] R. Talluri, K. Oehler, T. Bannon, J.D. Courtney, A. Das, and J. Liao, “A robust, scalable, object-based video compression technique for very low bit-rate coding,” IEEE Transactions on Circuits and Systems for Video Technique, Vol. 7, No. 1, pp. 221-233, Feb. 1997.
[7] B. Furht, J. Greenberg, and R. Westwater, “Motion Estimation Algorithms for Video Compression,” Kluwer Academic Publishers, Norwell, MA, pp.61-67, 1997.
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