756 resultados para Construction set
Resumo:
Faces are complex patterns that often differ in only subtle ways. Face recognition algorithms have difficulty in coping with differences in lighting, cameras, pose, expression, etc. We propose a novel approach for facial recognition based on a new feature extraction method called fractal image-set encoding. This feature extraction method is a specialized fractal image coding technique that makes fractal codes more suitable for object and face recognition. A fractal code of a gray-scale image can be divided in two parts – geometrical parameters and luminance parameters. We show that fractal codes for an image are not unique and that we can change the set of fractal parameters without significant change in the quality of the reconstructed image. Fractal image-set coding keeps geometrical parameters the same for all images in the database. Differences between images are captured in the non-geometrical or luminance parameters – which are faster to compute. Results on a subset of the XM2VTS database are presented.
Resumo:
Collaboration is acknowledged as a key to continued growth in the Australian construction industry. Government, as a major industry client, has an important role to play with respect to fostering collaboration and ensuring the global competitiveness of the industry. The paper draws upon data collected for the Construction 2020 study and aims to demonstrate that government can a) help to break down the adversarial situation that currently exists between clients, project managers and subcontractors; and b) allow the supply chain to collaborate more effectively in terms of satisfying the relational and financial needs of all parties. Government can also provide a clear set of guidelines (backed up by a functional dispute resolution system) that will promote confidence with respect to forging relationships. Thus, the paper will discuss the way in which public policy can be more closely aligned with actual industry needs in order to promote greater collaboration.