Adaptive optical flow for person tracking

Person tracking systems are dependent on being able to locate a person accurately across a series of frames. Optical flow can be used to segment a moving object from a scene, provided the expected velocity of the moving object is known; but successful detection also relies on being able segment the background. A problem with existing optical flow techniques is that they don’t discriminate the foreground from the background, and so often detect motion (and thus the object) in the background. To overcome this problem, we propose a new optical flow technique, that is based upon an adaptive background segmentation technique, which only determines optical flow in regions of motion. This technique has been developed with a view to being used in surveillance systems, and our testing shows that for this application it is more effective than other standard optical flow techniques.

From concept to embodiment : challenge and strategy

Facing with the difficulty in information propagation and synthesizing from conceptual to embodiment design, this paper introduces a function-oriented, axiom based conceptual modeling scheme. Default logic reasoning is exploited for recognition and reconstitution of conceptual product geometric and topological information. The proposed product modeling system and reasoning approach testify a methodology of "structural variation design", which is verified in the implementation of a GPAL (Green Product All Life-cycle) CAD system. The GPAL system includes major enhancement modules of a mechanism layout sketching method based on fuzzy logic, a knowledge-based function-to-form mapping mechanism and conceptual form reconstitution paradigm based on default geometric reasoning. A mechanical hand design example shows a more than 20 times increase in design efficacy with these enhancement modules in the GPAL system on a general 3D CAD platform.

Queensland's Smart State Initiative : a successful knowledge based urban development strategy

The chapter will set out to explain the KBUD and urban policy making processes in Queensland, Australia. This chapter will draw on providing a clear understanding on policy frameworks and relevant ICT applications of the Queensland ‘Smart State’ experience. The chapter is consisted of six sections. The first section following the introduction provides background information. The second section focuses on the KBUD processes in Queensland. The third section offers a comprehensive analysis of the ‘Queensland Smart State’ initiative, and it also identifies actors and goals of the agenda of Smart State experience. The fourth section reviews knowledge based development and ICT applications and policies of the Queensland Smart State and Brisbane Smart City experiences, and their impacts on Brisbane’s successful KBUD. The fifth section discusses knowledge hubs and ICT developments within the Brisbane metropolitan area. Then the chapter concludes with future trends and conclusion sections.