A Human Fall Detection System Using an Omni-Directional Camera in Practical Environments
| Autor: | Yi-Chang Huang, 黃逸昌 |
|---|---|
| Rok vydání: | 2008 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 96 In recent years, the number of the elderly increases rapidly. Consequently the health care of the elderly attracts more and more attention and we need to invest a lot of resources to maintain its quality. This thesis proposes a vision-based fall detection system using an omni-directional camera for the elderly and patients at home and in health-care institutions, hoping to detect the fall accident immediately when it happens and notify the medical personnel to provide the emergency care in time. In order to make the system more practical in real environments, we consider the practical environmental factors that may take place in our daily life. For instance, the occurrence of light source glimmer and turning a light on and off and leaving over static abandoned objects in the environment and resulting in multiple targets. The former can be solved by detecting the degree of luminance changes and the latter can be solved by using the static characteristic of abandoned objects. In addition we divide the fall down patterns in omni-directional images into non-radial and radial directions according to the angle associated with a body line. We further categorize the radial fall down patterns into inward and outward directions. We extract suitable features for these three different fall down patterns, including angle and length variation associated with the body line and Motion History Images. Given these features, a simple thresholding and decision tree technique is adopted for fall detection. Experimental results show that the proposed system has overcome the practical environmental factors of light source glimmer and static abandoned objects, increasing the practicability of the system in a real-world environment. In fall-down detection, since multiple fall-down patterns are considered, the recognition accuracy of the fall down system is improved from 0.73 to 0.87 and the Kappa value is improved from 0.47 to 0.75. These results show that we have proposed an effective fall down detecting system in this thesis. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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