Practical 3D reconstruction based on photometric stereo

Photometric Stereo is a powerful image based 3D reconstruction technique that has recently been used to obtain very high quality reconstructions. However, in its classic form, Photometric Stereo suffers from two main limitations: Firstly, one needs to obtain images of the 3D scene under multiple different illuminations. As a result the 3D scene needs to remain static during illumination changes, which prohibits the reconstruction of deforming objects. Secondly, the images obtained must be from a single viewpoint. This leads to depth-map based 2.5 reconstructions, instead of full 3D surfaces. The aim of this Chapter is to show how these limitations can be alleviated, leading to the derivation of two practical 3D acquisition systems: The first one, based on the powerful Coloured Light Photometric Stereo method can be used to reconstruct moving objects such as cloth or human faces. The second, permits the complete 3D reconstruction of challenging objects such as porcelain vases. In addition to algorithmic details, the Chapter pays attention to practical issues such as setup calibration, detection and correction of self and cast shadows. We provide several evaluation experiments as well as reconstruction results. © 2010 Springer-Verlag Berlin Heidelberg.

Knowledge acquisition in international strategic alliances among Malaysian manufacturing firms

This thesis examines the process of knowledge acquisition by Malaysian manufacturing firms through their involvement in international strategic alliances. The strategic alliances can be with or without equity involvement. Firms involved with a foreign partner with equity involvement are joint venture firms while non-equity involvement are firms that engaged in contractual agreements. Using empirical evidence from 65 international alliances gathered through a survey conducted in high-technology manufacturing sectors, several factors that influence the process of knowledge acquisition are examined. The factors are: learning capacity, experience, goals, active involvement and accessibility to the foreign knowledge. Censored regression analysis and ordered probit analysis are used to analyse the effects of these factors on knowledge acquisition and its determinant parts, and the effects of knowledge acquisition and its determinants on the performance of the alliances. A second questionnaire gathered evidence relating to the factors, which encouraged tacit knowledge transfer between the foreign and Malaysian partners in international alliances. The key findings of the study are: knowledge acquisition in international strategic alliances is influenced by five determining factors; learning capacity, experience, articulated goals, active involvement and accessibility; new technology knowledge, product development knowledge and manufacturing process knowledge are influenced differently by the determining factors; knowledge acquisition and its determinant factors have a significant impact on the firm’s performance; cultural differences tend to moderate the effect on the firm’s performance; acquiring tacit knowledge is not only influenced by the five determinant factors but also by other factors, such as dependency, accessibility, trust, manufacturing control, learning methods and organisational systems; Malaysian firms involved in joint ventures tend to acquire more knowledge than those involved in contractual agreements, but joint ventures also exhibit higher degrees of dependency than contractual agreements; and the presence of R&D activity in the Malaysian partner encourages knowledge acquisition, but the amount of R&D expenditure has no effect on knowledge acquisition.

Knowledge management for more sustainable water systems

The management and sharing of complex data, information and knowledge is a fundamental and growing concern in the Water and other Industries for a variety of reasons. For example, risks and uncertainties associated with climate, and other changes require knowledge to prepare for a range of future scenarios and potential extreme events. Formal ways in which knowledge can be established and managed can help deliver efficiencies on acquisition, structuring and filtering to provide only the essential aspects of the knowledge really needed. Ontologies are a key technology for this knowledge management. The construction of ontologies is a considerable overhead on any knowledge management programme. Hence current computer science research is investigating generating ontologies automatically from documents using text mining and natural language techniques. As an example of this, results from application of the Text2Onto tool to stakeholder documents for a project on sustainable water cycle management in new developments are presented. It is concluded that by adopting ontological representations sooner, rather than later in an analytical process, decision makers will be able to make better use of highly knowledgeable systems containing automated services to ensure that sustainability considerations are included.

Innovation, networking and globalisation:the role of regional innovation systems in the global innovation process

In the global economy, innovation is one of the most important competitive assets for companies willing to compete in international markets. As competition moves from standardised products to customised ones, depending on each specific market needs, economies of scale are not anymore the only winning strategy. Innovation requires firms to establish processes to acquire and absorb new knowledge, leading to the recent theory of Open Innovation. Knowledge sharing and acquisition happens when firms are embedded in networks with other firms, university, institutions and many other economic actors. Several typologies of innovation and firm networks have been identified, with various geographical spans. One of the first being modelled was the Industrial Cluster (or in Italian Distretto Industriale) which was for long considered the benchmark for innovation and economic development. Other kind of networks have been modelled since the late 1970s; Regional Innovation Systems represent one of the latest and more diffuse model of innovation networks, specifically introduced to combine local networks and the global economy. This model was qualitatively exploited since its introduction, but, together with National Innovation Systems, is among the most inspiring for policy makers and is often cited by them, not always properly. The aim of this research is to setup an econometric model describing Regional Innovation Systems, becoming one the first attempts to test and enhance this theory with a quantitative approach. A dataset of 104 secondary and primary data from European regions was built in order to run a multiple linear regression, testing if Regional Innovation Systems are really correlated to regional innovation and regional innovation in cooperation with foreign partners. Furthermore, an exploratory multiple linear regression was performed to verify which variables, among those describing a Regional Innovation Systems, are the most significant for innovating, alone or with foreign partners. Furthermore, the effectiveness of present innovation policies has been tested based on the findings of the econometric model. The developed model confirmed the role of Regional Innovation Systems for creating innovation even in cooperation with international partners: this represents one of the firsts quantitative confirmation of a theory previously based on qualitative models only. Furthermore the results of this model confirmed a minor influence of National Innovation Systems: comparing the analysis of existing innovation policies, both at regional and national level, to our findings, emerged the need for potential a pivotal change in the direction currently followed by policy makers. Last, while confirming the role of the presence a learning environment in a region and the catalyst role of regional administration, this research offers a potential new perspective for the whole private sector in creating a Regional Innovation System.

Knowledge management for more sustainable water systems

The management and sharing of complex data, information and knowledge is a fundamental and growing concern in the Water and other Industries for a variety of reasons. For example, risks and uncertainties associated with climate, and other changes require knowledge to prepare for a range of future scenarios and potential extreme events. Formal ways in which knowledge can be established and managed can help deliver efficiencies on acquisition, structuring and filtering to provide only the essential aspects of the knowledge really needed. Ontologies are a key technology for this knowledge management. The construction of ontologies is a considerable overhead on any knowledge management programme. Hence current computer science research is investigating generating ontologies automatically from documents using text mining and natural language techniques. As an example of this, results from application of the Text2Onto tool to stakeholder documents for a project on sustainable water cycle management in new developments are presented. It is concluded that by adopting ontological representations sooner, rather than later in an analytical process, decision makers will be able to make better use of highly knowledgeable systems containing automated services to ensure that sustainability considerations are included. © 2010 The authors.

Firms’ innovation objectives and knowledge acquisition strategies:a comparative analysis

External partnerships play an important role in firms’ acquisition of the knowledge inputs to innovation. Such partnerships may be interactive – involving exploration and mutual learning by both parties – or non-interactive – involving exploitative activity and learning by only one party. Examples of non-interactive partnerships are copying or imitation. Here, we consider how firms’ innovation objectives influence their choice of interactive and/or non-interactive connections. We conduct a comparative analysis for the economies of Spain and the UK, which have contrasting innovation eco-systems and regulation burdens.