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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 鄭國揚(Kuo-Young Cheng) | |
| dc.contributor.author | Hai-Feng Kao | en |
| dc.contributor.author | 高海峰 | zh_TW |
| dc.date.accessioned | 2021-06-13T05:48:05Z | - |
| dc.date.available | 2006-07-14 | |
| dc.date.copyright | 2006-07-14 | |
| dc.date.issued | 2006 | |
| dc.date.submitted | 2006-07-09 | |
| dc.identifier.citation | [1] Liang Zhao, “Dressed Human Modeling, Detection, and Parts Localization”, PhD thesis, 2001
[2] Manish Singh, Gregory D. Seyranian, and Donald D. Hoffman, “Parsing silhouettes: The short-cut rule”, Perception and Psychophysics, 1999 [3] Donald D. Hoffman, and Manish Singh, “Salience of Visual Parts”, Cognition, 1997 [4] Hillel Shaul Rom, “Part Decomposition and Shape Description”, PhD Thesis, 1993 [5] P.L. Rosin, “Shape partitioning by convexity”, IEEE Transactions on Systems, Man and Cybernetics, part A, pp.202–210, 2000 [6] Hsueh-Yi Sean Lin, Hong-Yuan Mark Liao, and Ja-Chen Lin, “Visual Salience-Guided Mesh Decomposition”, ICME workshop, 2004 [7] Evangelos Milios, and Euripides Petrakis, “Efficient Shape Matching and Retrieval at Multiple Scales”, Technical Report CS-1998-11, 1998 [8] Longin Jan Latecki, and Rolf Lak¨amper, “Convexity Rule for Shape Decomposition Based on Discrete Contour Evolution”, Computer Vision and Image Understanding Vol. 73, No. 3, March, pp. 441–454, 1999 [9] Longin Jan Latecki, and Rolf Lak¨amper, “Shape Similarity Measure Based on Correspondence of Visual Parts”, IEEE Transactions on Pattern analysis and Machine Intelligence, Vol 22, No. 10, October 2000 [10] J.C. Perez, E. Vidal, 'Optimum polygonal approximation of digitized curves', Pattern Recognition Letters, no.15, pp. 743-750 , 1994 [11] R. L. Ogniewicz, and O. Kubler, ”Hierarchic Voronoi skeletons”, Pattern Recognition. Vol. 28, no. 3, pp. 343-359. 1995 [12] K. Siddiqi and B.B. Kimia, “Parts of Visual Form: Computational Aspects,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 17, no. 3, pp. 239-251, March 1995 [13] S.M. Pizer, W.R. Oliver, and S.H. Bloomberg, “Hierarchical Shape Description via the Multiresolution Symmetric Axis Transform,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 9, no. 4, pp. 505-511, July 1987. [14] M. Brady, “Representing shape”, IEEE International Conference on Robotics and Automation. Proceedings, Volume 1, pp.256–265, Mar 1984 [15] H. Rom, G. Medioni, ”Hierarchical decomposition and axial shape description”, Pattern Analysis and Machine Intelligence, IEEE Transactions on Volume 15, Issue 10, pp.973 – 981, Oct. 1993 [16] H. Blum, “A Transformation for Extracting New Descriptors of Shape”, MIT Press, Cambridge, MA, 1967 [17] H. Blum and R. N. Nagel, “Shape description using weighted symmetric axis features”, Pattern Recognition, pp.167–180, 1978. [18]M. Brady and H. Asada, “Smoothed local symmetries and their implementation”, The International Journal of Robotics Research, pp.36–61, 1984. [19] R. A. Brooks, “Symbolic reasoning among 3-D models and 2-D images”, Artificial Intelligence, pp.285–348, 1981. [20] R. A. Brooks, “Model-based three dimensional interpretations of two dimensional images”, IEEE Transactions on Pattern Analysis and Machine Intelligence, pp.140–150, 1983. [21] D. D. Hoffman and W. A. Richards, “Parts of recognition”, Cognition 18, p.p. 65–96, 1984 [22] Tyng-Luh Liu and Davi Geiger and Robert Kohn, “Representation and self-similarity of shape”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 25, Issue 1, pp. 86 – 99, Jan. 2003 [23] K. Siddiqi, K. Tresness, and B. B. Kimia, “Parts of visual form: Psychophysical aspects”, Perception 25, pp. 399–424, 1996 [24] E. Milios and E.G.M. Petrakis, “Shape retrieval based on dynamic programming” IEEE Transactions on Image Processing., vol. 9, no. 1, pp. 141–146, 2000. [25] M. Keil, “Polygon decomposition”, In J.-R. Sack and J. Urrutia, editors, Handbook of Computational Geometry. Elsevier Science Publishers B.V. North-Holland,Amsterdam, pp. 29–78, 1999 [26] Thomas B. Sebastian, Philip N. Klein, and Benjamin B. Kimia, 'Alignment-based recognition of shape outlines,' IWVF, pp. 606-618, 2001 [27] G. Mori, S. Belongie, J. Malik, “Efficient shape matching using shape contexts”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 27, Issue 11, pp.1832 – 1837, 2005 [28] Haibin Ling, David W. Jacobs, “Using the Inner-Distance for Classification of Articulated Shapes”, CVPR, pp.719-726, 2005 [29] R. A. Brooks, 'Symbolic reasoning among 3-D models and 2-D images,' Artificial Intell., vol. 17, pp. 285-348, 1981 | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/33881 | - |
| dc.description.abstract | 在這個世界上有很多物體是由更小形狀更簡單的部份所組成的。如果可以找出這些物體的是由哪些部分所組成，將有助於物件的搜尋和檢索。在本論文中，我們試著把一個物體投影在二維平面上的形狀的各個部份的結構給找出來。和之前的作品不同的地方在於我們把這個抽象的問題轉化為數學上最佳化的問題，並提出一個多項式時間內的演算法來解決這個問題。這個演算法也可以整合對該類物體有關的知識或加入其他的限制來達到更好的效果。 | zh_TW |
| dc.description.abstract | There are many objects which are composed of several primitive parts. It’s always beneficial to find the inherent structure of objects when dealing with the recognition, searching or indexing issues of the objects. This thesis aims to recover the intuitive and natural parts from the 2D shapes of objects. This thesis is different from the previous approaches via characterizing the traditional shape decomposition problem as an optimization problem. Building on the foundation of visual salience, our work shows that, the optimal solution of shape decomposition can be solved efficiently by dynamic programming when a set of pre-defined constraints is satisfied. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-13T05:48:05Z (GMT). No. of bitstreams: 1 ntu-95-R93922043-1.pdf: 957743 bytes, checksum: d69e071b7fc686bd3ea7e80c0a2b7d9c (MD5) Previous issue date: 2006 | en |
| dc.description.tableofcontents | Chapter 1 Introduction 3
1.1 Motivation and Goal.........................................3 1.2 Shape Decomposition.........................................5 1.2.1 Definition of Parts.......................................5 1.2.2 The non-uniqueness of shape decomposition.................7 1.2.3 Criteria for good shape decomposition algorithm...........8 1.3 Dissertation Overview.......................................9 Chapter 2 Review on Previous Work 11 2.1 Overview...................................................11 2.2 Visual Salience and Minimum Rule...........................11 2.2.1 The Minima Rule..........................................12 2.2.2 Boundary Strength........................................14 2.2.3 Relative Size............................................17 2.2.4 Protrusion...............................................17 2.3 The Extensions from Visual Salience........................18 2.4 Other Works on 2D Shape Decomposition......................20 Chapter 3 Optimization Formulation for Shape Decomposition .23 3.1 Overview...................................................23 3.2 The Optimization Formulation for Shape Decomposition.......23 3.3 The Star Shapes............................................25 3.4 Shape Decomposition for Star Shapes........................26 3.4.1 Decomposition............................................26 3.4.2 The Determination of Start Point.........................31 3.4.3 The Determination of Cut Number..........................31 3.5 The Computation Difficulty of the Optimization Formulation.32 Chapter 4 Experiment 35 4.1 Overview...................................................35 4.2 The Salience Function......................................35 4.3 Experiment Results.........................................36 4.4 Discussion.................................................43 Chapter 5 Discussion and Conclusions 47 5.1 The Extensions of Star Shape Decomposition.................47 5.2 Limitations of Star Shape Decomposition....................48 5.3 Comparison with Previous Work..............................48 5.4 Conclusion.................................................49 Bibliography.....................51 | |
| dc.language.iso | en | |
| dc.subject | 形狀分割 | zh_TW |
| dc.subject | 形狀分解 | zh_TW |
| dc.subject | 動態規劃 | zh_TW |
| dc.subject | 物件檢索 | zh_TW |
| dc.subject | object retrieval | en |
| dc.subject | shape segmentation | en |
| dc.subject | shape decomposition | en |
| dc.subject | dynamic programming | en |
| dc.title | 以最佳化觀點及人類感知為基礎之平面星狀形分解切割 | zh_TW |
| dc.title | Using Dynamic Programming to Segment Planar Star Shape Based on Human Perception and Optimization Formulation | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 94-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.coadvisor | 廖弘源(Hong-Yuan Mark Liao) | |
| dc.contributor.oralexamcommittee | 郭大維(Tei-Wei Kuo),劉庭祿(Tyng-Luh Liu) | |
| dc.subject.keyword | 形狀分割,形狀分解,動態規劃,物件檢索, | zh_TW |
| dc.subject.keyword | shape segmentation,shape decomposition,dynamic programming,object retrieval, | en |
| dc.relation.page | 53 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2006-07-11 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 資訊工程學研究所 | zh_TW |
| 顯示於系所單位： | 資訊工程學系 | |
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