The grounded theory alternative in business network research

This paper presents a brief outline of the defining characteristics of grounded theory methodology. Such a focus was motivated by a desire to bring the methodology into clearer focus. Particular attention is paid to the debate grounded theory has engendered. In doing so, a number of misunderstandings, dilemmas and criticisms are highlighted. Thus, while one research strategy should not be emphasised to the exclusion of others, this paper advocates the use of grounded theory methodology as a fresh approach in addressing some of the research challenges associated with network studies

Coherent segmentation of video into syntactic regions

In this paper we report on our work in realising an approach to video shot matching which involves automatically segmenting video into abstract intertwinded shapes in such a way that there is temporal coherency. These shapes representing approximations of objects and background regions can then be matched giving fine-grained shot-shot matching. The main contributions of the paper are firstly the extension of our segmentation algorithm for still images to spatial segmentation in video, and secondly the introduction a measurement of temporal coherency of the spatial segmentation. This latter allows us to quantitatively demonstrate the effectiveness of our approach on real video data

Coherent Segmentation of Video into Syntactic Regions

In this paper we report on our work in realising an approach to video shot matching which involves automatically segmenting video into abstract intertwinded shapes in such a way that there is temporal coherency. These shapes representing approximations of objects and background regions can then be matched giving fine-grained shot-shot matching. The main contributions of the paper are firstly the extension of our segmentation algorithm for still images to spatial segmentation in video, and secondly the introduction a measurement of temporal coherency of the spatial segmentation. This latter allows us to quantitatively demonstrate the effectiveness of our approach on real video data.

Coherent segmentation of video into syntactic regions

In this paper we report on our work in realising an approach to video shot matching which involves automatically segmenting video into abstract intertwinded shapes in such a way that there is temporal coherency. These shapes representing approximations of objects and background regions can then be matched giving fine-grained shot-shot matching. The main contributions of the paper are firstly the extension of our segmentation algorithm for still images to spatial segmentation in video, and secondly the introduction a measurement of temporal coherency of the spatial segmentation. This latter allows us to quantitatively demonstrate the effectiveness of our approach on real video data