利用人物形狀在時間與空間的變化來偵測打滑與跌倒事件

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研究生：	廖翊廷 Liao, Yi-Ting
論文名稱：	利用人物形狀在時間與空間的變化來偵測打滑與跌倒事件 Slip and Fall Detection using Spatiotemporal Characteristics of Human Object for video Surveillance System
指導教授：	黃仲陵 Huang, Chung-Lin
口試委員:
學位類別：	碩士 Master
系所名稱：	電機資訊學院 - 電機工程學系 Department of Electrical Engineering
論文出版年：	2009
畢業學年度：	97
語文別：	英文
論文頁數：	58
中文關鍵詞：	打滑事件偵測、跌倒事件偵測、型態分析
外文關鍵詞：	Slip Event Detection, Fall Event Detection, Integrated Spatiotemporal Energy (ISTE) map, Shape Analysis
相關次數：	點閱：3 下載：0
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一個智慧型居家監控安全系統所涵蓋的室內環境裡，異常事件的發生可能與人員的行為相關，也可能無關(如室內環境的異常)。跌倒事件可能造成人員受傷甚至使人員不具有行動能力，老年人跌倒時更是我們需要給予協助的。為了提升看護的醫療品質，降低看護人員因為疲勞所造成的疏失，因此本論文主要偵測人員打滑事件與跌倒事件並發出警訊尋求看護人員的協助。
系統首先分析監視器所拍攝的人員的行為活動，然後判斷是否有打滑的事件發生，倘若人員打滑我們將進一步分析該人員是否有跌倒事件發生，如果是，則即時通告看護人員予以警示並給予其人員適當的協助。在居家環境或老人療養院中，經由攝影機裝置及影像分析的技術，便可以用來偵測環境中的一些危險的動作以及不尋常的行為，比如說，爬樓梯時跌倒與走路時滑倒，這些危險的行為若經由影像分析，便可以即時的通知相關人員，從而避免許多意外的發生。
在本論文中，我們提出Integrated Spatiotemporal Energy (ISTE) map判定受監控的環境之下的人員是否有不尋常的大動作變換。若有大動作的變換我們判定為有可能發生異常事件，利用適合的橢圓代表受監控的人員進而分析該人員的型態，分析該橢圓所具有的參數─ 長軸、短軸、長軸與水平方向的夾角，偵測打滑的事件與跌倒的事件。在實際監視系統裡面，因為影像傳輸的過程中的frame rate不固定，在此情況下利用ISTE map仍能正確定義出該人員的動量變化程度。

Fall and slip of the elderly are the main concerns for home care or day care center. We proposed a method to detect a slip event and a fall event by computing integrated spatiotemporal energy (ISTE) map that includes motion and time of motion occurrence as our motion feature. The extracted human shape is represented by an ellipse that provides crucial information of human motion activities. We use this features to detect the events in the video with non-fixed frame rate. In this work, we assume that the person is on the ground with no or little motion after the fall accident. Our experiments are demonstrated in the indoor and the outdoor scenes, where the illuminate condition varies. So the threshold of the background subtraction and the parameters of the smoothing filter are adjusted independently. Experimental results show that our method is effective for fall and slip detection. The total number of testing frames is about , and we use an Intel Core2 Duo 1.8GHz CPU on a Microsoft Windows XP operating system.

Abstract...................................................i
Contents..................................................ii
List of Figures..........................................iii
List of Tables............................................vi

Chapter 1 Introduction.....................................1

Chapter 2 Foreground Extraction............................6
2.1 Background Subtraction.................................6
2.2 Foreground Object Pre-processing.......................8
2.2.1 Morphological Filtering..............................8
2.2.2 Labeling............................................10

Chapter 3 Motion Information..............................12
3.1 Normalization.........................................12
3.2 Integrated Spatiotemporal Energy Map..................15
3.3 Comparison with Other Motion Activity Measures........26

Chapter 4 Human Object Shape Analysis.....................30
4.1 The Center of the Ellipse.............................30
4.2 The Angle of the Ellipse..............................32
4.3 The Semi-axis of the Ellipse..........................33

Chapter 5 Slip and Fall Detection.........................37
5.1 Slip Detector.........................................37
5.2 Fall Detector.........................................39

Chapter 6 Experimental Results............................42
6.1 Experiment 1 : Object moving inside the scene continuously..............................................46
6.2 Experiment 2 : Object moving out of the scene.........48
6.3 Experiment 3 : Camera is not stationary...............50
6.4 Experiment 4 : Human object sitting down..............52

Chapter 7 Conclusion and Future Works.....................56

References................................................57

                                

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