本文中，一個低成本和高效率的系統性自動分析半管運動轉播影片方法被提出來。除了場地顏色覆蓋比率，我們發現玩家區域使用顯著目標偵測機制可面對半管運動影片模糊場景的挑戰。此外，基於現有的MPEG 壓縮的影片原生的運動向量（motion vector）我們提出一種可用於偵測旋轉（spin）事件的新穎且有效的方法。實驗結果表明，該系統能有效在半管影片中識別難以被檢測到的旋轉（spin）和滑行（grind）等事件。

In this work, a low-cost and efficient system is proposed to automatically analyze the halfpipe sports broadcasting videos. In addition to the court color ratio information, we find the player region by using salient object detection mechanisms for facing the challenge of motion blurred scenes in HP videos. Besides, a novel and efficient method for detecting the spin event is proposed on the basis of native motion vectors existing in MPEG compressed video. Experimental results show that the proposed system is effective in recognizing the hard-to-be-detected spin and grind events in halfpipe videos.

口試委員會審定書i
誌謝ii
摘要iii
Abstract iv
1 Introduction 1
1.1 What is a Halfpipe? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 What is a Trick? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.3 How to Learn a Trick . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.4 The Problem of Watching Halfpipe Broadcasting Videos . . . . . . . . . 5
1.5 How to Solve Watching Halfpipe Broadcasting Videos Problems . . . . . 6
1.6 Challenges of Event Detection in Halfpipe Videos . . . . . . . . . . . . . 6
2 Related Work 7
3 Proposed Method 9
3.1 Highest Point Detection and Trick Segmentation . . . . . . . . . . . . . . 9
3.1.1 Noise Elimination . . . . . . . . . . . . . . . . . . . . . . . . . 9
3.1.2 Peak and Valley Detection . . . . . . . . . . . . . . . . . . . . . 10
3.2 Player Detection and Tracking . . . . . . . . . . . . . . . . . . . . . . . 10
3.3 Spin Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
3.4 Grind Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
4 Results and Discusion 13
4.1 Cut Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
4.2 Highest Point Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
4.3 Spin Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
4.4 Grind Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
5 Conclusion and Future Work 19
Bibliography 21

[1] U. Gargi, R. Kasturi, and S. H. Strayer. Performance characterization of videoshot-
change detection methods. Circuits and Systems for Video Technology, IEEE
Transactions on, 10(1):1–13, 2000.
[2] J. Harding, C. Mackintosh, A. Hahn, and D. James. Classification of aerial acrobatics
in elite half-pipe snowboarding using body mounted inertial sensors. In The
Engineering of Sport 7, pages 447–456. Springer Paris, 2008.
[3] T. Holleczek, J. Schoch, B. Arnrich, and G. Troster. Recognizing turns and other
snowboarding activities with a gyroscope. In Wearable Computers (ISWC), 2010
International Symposium on, pages 1–8. IEEE, 2010.
[4] I. Koprinska and S. Carrato. Temporal video segmentation: A survey. Signal processing:
Image communication, 16(5):477–500, 2001.
[5] H. Li, J. Tang, S. Wu, Y. Zhang, and S. Lin. Automatic detection and analysis of
player action in moving background sports video sequences. Circuits and Systems
for Video Technology, IEEE Transactions on, 20(3):351–364, 2010.
[6] T. Liu, Z. Yuan, J. Sun, J. Wang, N. Zheng, X. Tang, and H.-Y. Shum. Learning to
detect a salient object. IEEE trans. PAMI, 33(2), 2011.
[7] J. Ning, L. Zhang, D. Zhang, and C. Wu. Robust mean-shift tracking with corrected
background-weighted histogram. Computer Vision, IET, 6(1):62–69, January 2012.
[8] N. Otsu. A threshold selection method from gray-level histograms. Automatica,
11(285-296):23–27, 1975.
[9] J. Turnbull, J. W. Keogh, and A. E. Kilding. Strength and conditioning considerations
for elite snowboard half pipe. Open Sports Medicine Journal, 5:1–11, 2011.
[10] L. Xie, S.-F. Chang, A. Divakaran, and H. Sun. Structure analysis of soccer video
with hidden markov models. In Acoustics, Speech, and Signal Processing (ICASSP),
2002 IEEE International Conference on, volume 4, pages IV–4096. IEEE, 2002.
[11] J. Zhang, J. Qiu, X. Wang, and L. Wu. Representation of the player action in sport
videos. In Signal and Information Processing Association Annual Summit and Conference
(APSIPA), 2013 Asia-Pacific, pages 1–4. IEEE, 2013.