透過您的圖書館登入
IP:3.21.106.69
  • 學位論文

運用色塊追蹤與分析辨識人體動作

Identifying Human Body Motion by Color Tracking and Region

指導教授 : 陳瑞發

摘要


近年來,微軟推出的Kinect利用內附的深度感測器,計算出人體的骨架,稱為深度骨架偵測,讓體感偵測的方式有更多元的變化,相關的研究不斷地提出與跟進,而動作的偵測與分析亦是探討的研究之一。 透過深度影像體感偵測,在進行部分動作時會無法偵測到,使得偵測動作時會發生誤判情形。例如:腳交叉、躺姿。為了改善此誤判情形,本論文透過影像顏色區塊的重心來達成動作的偵測,確保追蹤的部分為身體的骨架,來達到顏色追蹤,以解決誤判和追蹤的問題,達到骨架的正確追蹤。

並列摘要


In recent years, using of Microsoft's Kinect depth sensor to calculate the human skeleton is called depth skeleton detection. So the way of somatosensory detection can more diverse. Related researches are constantly raised and follow-up, and the action of the detection and analysis is also discussed. There are some motions cannot be detected by the skeleton from depth image, for example, foot-cross and lying will cause judgment failed. In order to improve this misjudgment, this thesis uses the centroid of the color regions to achieve the motion detection. Ensuring the tracking point is the skeleton of the body to achieve the color tracking and solving the problem of misjudgment and tracking. Let the skeleton be tracked correctly.

參考文獻


(NAFIPS), 2010 Annual Meeting of the North American,
[2]Raphael Gonzalez, Richard E. Woods , “Digital Image
[1]Booth Paul A., “An Introduction To Human-Computer
Interaction,” Psychology Press, 1989.
18075-8, p.295, 2002.

被引用紀錄


林羽靖(2014)。音樂指揮軌跡之機器學習─以Kinect為例〔碩士論文,淡江大學〕。華藝線上圖書館。https://doi.org/10.6846/TKU.2014.00866

延伸閱讀