Canberra's Afterlife. Highpressure Crystals and the Bush Capital Dream

Canberra, the ?Bush Capital? of Australia, was a project torn between ambition and avoidance. For fear of upsetting Sydney or Melbourne, its location avoided larger territorial aspirations but its crystalline winning scheme was bold, and contained the promise of enlightened irradiation. Postwar Canberra, like so many other cities at the time, let its future be designed by Cold-War traffic engineers, who confidently turned dream into sprawl and highways. Although Canberra s mix of ambition and banality, of symbolic desire and structural normalcy, may be precisely what a good city is all about, it probably contains these in defective proportions. What Canberra needs is just a little more of itself, in different amounts, to a higher pressure from the inside. We can easily imagine the multiplying of the original Griffin plan, adding the city onto itself, organizing the recent sprawl with new nodes and public transport with more urban streets between them. With this reclaimed space for higher density, Canberra can then grow from the inside instead of sprawling away, lowering its expenditure on transport and its carbon and sustainability footprint. The new nodes will be denser and allow for variety and change in its programmatic design. Minor but detailed changes in street and public space design will also allow for easier multi-species (people, animals?) access to urban and natural resources. Video brief of the project: http://vimeo.com/45799435

Robust Real-time Vision-based Aircraft Tracking From Unmanned Aerial Vehicles.

Aircraft tracking plays a key and important role in the Sense-and-Avoid system of Unmanned Aerial Vehicles (UAVs). This paper presents a novel robust visual tracking algorithm for UAVs in the midair to track an arbitrary aircraft at real-time frame rates, together with a unique evaluation system. This visual algorithm mainly consists of adaptive discriminative visual tracking method, Multiple-Instance (MI) learning approach, Multiple-Classifier (MC) voting mechanism and Multiple-Resolution (MR) representation strategy, that is called Adaptive M3 tracker, i.e. AM3. In this tracker, the importance of test sample has been integrated to improve the tracking stability, accuracy and real-time performances. The experimental results show that this algorithm is more robust, efficient and accurate against the existing state-of-art trackers, overcoming the problems generated by the challenging situations such as obvious appearance change, variant surrounding illumination, partial aircraft occlusion, blur motion, rapid pose variation and onboard mechanical vibration, low computation capacity and delayed information communication between UAVs and Ground Station (GS). To our best knowledge, this is the first work to present this tracker for solving online learning and tracking freewill aircraft/intruder in the UAVs.