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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/43581完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 洪一平(Yi-Ping Hung) | |
| dc.contributor.author | Yun-Chien Lai | en |
| dc.contributor.author | 賴韻芊 | zh_TW |
| dc.date.accessioned | 2021-06-15T02:23:48Z | - |
| dc.date.available | 2012-08-20 | |
| dc.date.copyright | 2009-08-20 | |
| dc.date.issued | 2009 | |
| dc.date.submitted | 2009-08-18 | |
| dc.identifier.citation | [1] T. B. Moeslund, A. Hilton, and V. Kruger, “A survey of advances in vision-based human motion capture and analysis,” Computer Vision and Image Understanding, 104(2):90-126, 2006.
[2] R. Poppe, “Vision-based human motion analysis: An overview.” Computer Vision and Image Understanding, 108:4-18, 2007. [3] W. T. Freeman and C.D. Weissman, “Television control by hand gestures,” IEEE Intl. Wkshp. On Automatic Face and Gesture Recognition, pp. 179-183, 1995. [4] C. Wren, A. Azarbayejani, T. Darrell, and A. Pentland,” Pfinder: Real-time tracking of the human body,” IEEE Trans. Pattern Anal. Mach. Intell. 19(7), 1997, 780–785. [5] M. Brand, N. Oliver, and A. Pentland, “Coupled hidden markov models for complex action recognition,” Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition, pp. 994–999, 1997. [6] K. Tollmar, D. Demirdjian, T. Darrell, “Navigating in virtual environments using a vision-based interface,” Nordic Conference on Human-Computer Interaction, Vol. 82, pp. 113-120, 2004. [7] Kalman, R. E. 1960. “A New Approach to Linear Filtering and Prediction Problems,” Transaction of the ASME—Journal of Basic Engineering, pp. 35-45 (March 1960). [8] S. Arulampalam,“A Tutorial on Particle Filters for On-line Non-linear/Non-Gaussian Bayesian Tracking,” IEEE Transactions on Signal Processing, Vol. 50, pp. 174-188, 2001. [9] M. Isard and A. Blake, “Condensation conditional density propagation for visual tracking,” International Journal of Computer Vision, Vol. 1, pp. 5-28, 1998. [10] R. Lienhart and J. Maydt, “An extended set of haar-like features for rapid object detection,” IEEE International Conference on Image Processing, vol. 1, pp. 900–903, 2002. [11] V. Vezhnevets, V. Sazonov, and A. Andreeva, “A survey on pixel-based skin color detection techniques,” Proc. Graphicon, pp. 85–92, 2003. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/43581 | - |
| dc.description.abstract | 在數位家庭的應用上，本篇論文提出一個方法來達到控制多媒體播放器的目的。此方法是以三維的人體模型為基礎，使用手勢辨識來提供一個直覺的控制方式。我們的動機是讓系統能夠察覺到使用者的意圖。為了追蹤使用者的手勢並且辨認這些手勢的含意以達到互動的控制系統的目的，貝式架構被運用在這個基於三維模型的手勢辨識系統中。另外，為了避免三維人體模型的高自由度可能造成手勢追蹤複雜化的問題，我們系統使用一個新的階層式演算法來增加系統效能。除此之外，這個系統應用多個特徵來增加追蹤的正確率。實驗結果可以看出本系統在於追蹤手勢是很穩定的，並且將來很有可能發展出一個控制多媒體的撥放器。 | zh_TW |
| dc.description.abstract | This paper presents a new approach to 3D model-based gesture recognition for controlling multimedia player. The motivation of this paper is to make home appliance aware of user’s intention. This 3D model-based gesture recognition system adopts a Bayesian framework to track the user’s hand posture and to recognize meaning of these postures for controlling 3D player interactively. To avoid the high dimensionality of the whole 3D upper body model, which may complicate the gesture tracking problem, our system applies a new hierarchical tracking algorithm to improve the system performance. Moreover, this system applies multiple cues for improving the accuracy of tracking results. Experimental results have shown that the proposed system tracks the hand posture robustly and has high application potential for controlling the multimedia player. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-15T02:23:48Z (GMT). No. of bitstreams: 1 ntu-98-R96944034-1.pdf: 2908764 bytes, checksum: f331736a1342017f71def83bcf57c4e3 (MD5) Previous issue date: 2009 | en |
| dc.description.tableofcontents | 口試委員會審定書 i
誌謝 ii 摘要 iii Abstract iv Contents v List of Figures vii 1 Introduction 1 2 Related Work 4 3 System Overview 8 4 Three Dimension Model for Upper Body 10 5 Tracking Based on Bayesian Filtering Framework 15 5.1 Bayesian Filtering Framework 16 5.2 Using Kalman Filtering for Head Tracking 18 5.2.1 Detection of Head Position 18 5.2.2 Head Tracking 20 5.3. Using Particle Filter for Arm Tracking 22 5.3.1 Introduction to Particle Filtering 22 5.3.2 Preprocessing 24 5.3.3 Palm Tracking 25 5.3.4 Elbow Tracking 29 6 Experiments 31 6.1 Using Kalman filter for Head Tracking 32 6.2 Three Approaches on Palm Tracking 33 7 Conclusion and Future Work 42 Bibliography 43 | |
| dc.language.iso | en | |
| dc.subject | 三維人體動作追蹤 | zh_TW |
| dc.subject | 粒子濾波器 | zh_TW |
| dc.subject | 姿態估計 | zh_TW |
| dc.subject | 3D human motion tracking | en |
| dc.subject | particle filtering | en |
| dc.subject | pose estimation | en |
| dc.title | 基於電腦視覺之手勢辨識系統 | zh_TW |
| dc.title | A Computer-Vision Based Gesture Recognition System | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 97-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 陳祝嵩,唐政元,黃于飛 | |
| dc.subject.keyword | 三維人體動作追蹤,姿態估計,粒子濾波器, | zh_TW |
| dc.subject.keyword | 3D human motion tracking,pose estimation,particle filtering, | en |
| dc.relation.page | 44 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2009-08-18 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 資訊網路與多媒體研究所 | zh_TW |
| 顯示於系所單位： | 資訊網路與多媒體研究所 | |
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| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-98-1.pdf 未授權公開取用 | 2.84 MB | Adobe PDF |
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