Intelligent computer vision processing techniques for fall detection in enclosed environments

Detecting unusual movement (falls) for elderly people in enclosed environments is receiving increasing attention and is likely to have massive potential social and economic impact. In this thesis, new intelligent computer vision processing based techniques are proposed to detect falls in indoor environments for senior citizens living independently, such as in intelligent homes. Different types of features extracted from video-camera recordings are exploited together with both background subtraction analysis and machine learning techniques. Initially, an improved background subtraction method is used to extract the region of a person in the recording of a room environment. A selective updating technique is introduced for adapting the change of the background model to ensure that the human body region will not be absorbed into the background model when it is static for prolonged periods of time. Since two-dimensional features can generate false alarms and are not invariant to different directions, more robust three-dimensional features are next extracted from a three-dimensional person representation formed from video-camera measurements of multiple calibrated video-cameras. The extracted three-dimensional features are applied to construct a single Gaussian model using the maximum likelihood technique. This can be used to distinguish falls from non-fall activity by comparing the model output with a single. In the final works, new fall detection schemes which use only one uncalibrated video-camera are tested in a real elderly person s home environment. These approaches are based on two-dimensional features which describe different human body posture. The extracted features are applied to construct a supervised method for posture classification for abnormal posture detection. Certain rules which are set according to the characteristics of fall activities are lastly used to build a robust fall detection model

3D reconstruction of coronary arteries from angiographic sequences for interventional assistance

Introduction -- Review of literature -- Research hypothesis and objectives -- Methodology -- Results and discussion -- Conclusion and future perspectives

What kind of information do drivers need? An investigation of drivers' information requirements in Kuala Lumpur, Malaysia

Past research indicated that driver information requirements were varied (e. g. Spyridakis et al., 1991) and the motorists population cannot be consider homogeneous in terms of information requirements (e. g. Haselkorn et al., 1991). Some of the previous studies even suggestedth at before the so-called intelligent systemsg o into production, several unresolved issues concerning what kind of information drivers require need to be resolved. Thus, this thesis is interested in exploring several human factors issues concerning drivers; ' information requirements. First, the study is trying to provide at least a general picture of what kind of information is suitable to be presented to drivers in certain types of journey. Secondly, the thesis is interested in exploring the suitable timing and mode to present the required information to the target audiences. Besides the aforementioned human factors issues, this research also investigated how drivers plan their routes and find their way in unfamiliar destinations. The study is also interested in examining criteria used by drivers in choosing a route to their intended destination. Finally, this thesis aims to measure respondents' behavioral responses when they were given several traffic messages on congestion while commuting to and from work. The results also revealed that local drivers used more than one strategy for route planning and wayfinding in unfamiliar locations. Maps were the main strategy used by most of the respondents who participated in this study. Other strategies used by respondents were asking a passer-by, relying on memory and going without preparation. Apart from that, this study also demonstrated the difficulty in arriving at a general conclusion concerning the appropriate criteria that drivers would use in selecting a route for different trips. Local drivers would use a variety types of criteria in order to choose a route to a particular destination. However, the thesis identifies that drivers mainly employed three types of criteria in selecting a route to a particular destination. These criteria were safety, saving mileage and avoiding congested routes The final study (Study 3) was interested in extending the results of both studies I and 2 particularly the presentationo f congestionm essagesto its end users,i . e. motorists. An experiment was conducted to investigate drivers' response towards the presentation of traffic messagesa bout congestion.T he findings clearly supportedp revious work that found different types of information are likely to elicit different kind of responses from the drivers. In addition, local drivers also had ideas about the design of future traffic messages on congestion. For example, the need to have a quick solution when faced with the problem, e. g. offer alternate route; the need to have information on travel time if they decided to use the alternate route recommended by the systems; and some of the messages should be given as early as possible to serve as pre-trip advanced warning to drivers. The findings clearly demonstrated the preference for having more information rather than less