Enhancing digital road map with lane details extracted from large-scale stereo aerial imagery using object-oriented image analysis

Precise, up-to-date and increasingly detailed road maps are crucial for various advanced road applications, such as lane-level vehicle navigation, and advanced driver assistant systems. With the very high resolution (VHR) imagery from digital airborne sources, it will greatly facilitate the data acquisition, data collection and updates if the road details can be automatically extracted from the aerial images. In this paper, we proposed an effective approach to detect road lane information from aerial images with employment of the object-oriented image analysis method. Our proposed algorithm starts with constructing the DSM and true orthophotos from the stereo images. The road lane details are detected using an object-oriented rule based image classification approach. Due to the affection of other objects with similar spectral and geometrical attributes, the extracted road lanes are filtered with the road surface obtained by a progressive two-class decision classifier. The generated road network is evaluated using the datasets provided by Queensland department of Main Roads. The evaluation shows completeness values that range between 76% and 98% and correctness values that range between 82% and 97%.

A new day breaks for the Aussie film industry

The Australian film industry is evolving. The days when government film agencies handed out millions of taxpayers' dollars for filmmakers to produce "Australian stories" with little regard to commercial returns are limited. If the Australian film industry is to reach mainstream audiences – and increase its relevance – then filmmakers need to take greater notice of genre movies and the possibilities they create within the financial restraints of the local industry. The $20 million Aussie vampire movie, Daybreakers, is a prototype for how this can be achieved.