Modelling human behaviour and event detection from videos

Automatic analysis of human behaviour in large collections of videos is gaining interest, even more so with the advent of file sharing sites such as YouTube. However, challenges still exist owing to several factors such as inter- and intra-class variations, cluttered backgrounds, occlusion, camera motion, scale, view and illumination changes. This research focuses on modelling human behaviour for action recognition in videos. The developed techniques are validated on large scale benchmark datasets and applied on real-world scenarios such as soccer videos. Three major contributions are made. The first contribution is in the area of proper choice of a feature representation for videos. This involved a study of state-of-the-art techniques for action recognition, feature extraction processing and dimensional reduction techniques so as to yield the best performance with optimal computational requirements. Secondly, temporal modelling of human behaviour is performed. This involved frequency analysis and temporal integration of local information in the video frames to yield a temporal feature vector. Current practices mostly average the frame information over an entire video and neglect the temporal order. Lastly, the proposed framework is applied and further adapted to real-world scenario such as soccer videos. A dataset consisting of video sequences depicting events of players falling is created from actual match data to this end and used to experimentally evaluate the proposed framework.

Governance and community capitals : understanding how governance has worked in three faith-based schools in the Western Highlands of Papua New Guinea

This thesis, titled Governance and Community Capitals, explores the kinds of practical processes that have made governance work in three faith-based schools in the Western Highlands of Papua New Guinea (PNG). To date, the nation of PNG has been unable to meet its stated educational goals; however, some faith-based primary schools have overcome educational challenges by changing their local governance systems. What constitutes good governance in developing countries and how it can be achieved in a PNG schooling context has received very little scholarly attention. In this study, the subject of governance is approached at the nexus between the administrative sciences and asset-based community development. In this space, the researcher provides an understanding of the contribution that community capitals have made to understandings of local forms of governance in the development context. However, by and large, conceptions of governance have a history of being positioned within a Euro-centric frame and very little, if anything is known about the naming of capitals by indigenous peoples. In this thesis, six indigenous community capitals are made visible, expanding the repertoire of extant capitals published to date. The capitals identified and named in this thesis are: Story, Wisdom, Action, Blessing, Name and Unity. In-depth insights into these capitals are provided and through the theoretical idea of performativity, the researcher advances an understanding of how the habitual enactment of the practical components of the capitals made governance work in this unique setting. The study draws from a grounded and appreciative methodology and is based on a case study design incorporating a three-stage cycle of investigation. The first stage tested the application of an assets-based method to documentary sources of data including most significant change stories, community mapping and visual diaries. In the second stage, a group process method relevant to a PNG context was developed and employed. The third stage involved building theory from case study evidence using content analysis, language and metaphorical speech acts as guides for complex analysis. The thesis demonstrates the contribution that indigenous community capitals can make to understanding local forms of governance and how PNG faith-based schools meet their local governance challenges.