Semantic change detection through large-scale learning (LP130100156)

ACVT has been awarded a 3 year ARC Linkage Project valued at $377,000. The industry partner is BAE Systems. The CIs on the project are Prof. Anton van den Hengel, Dr Chunhua Shen, Dr Anders Eriksson and Dr Qinfeng Shi.

Identifying whether there has been a significant change in a scene from a set of images is an important practical task, and has received much attention. The problem has been, however, that although existing statistical techniques perform reasonably well, it has been impossible to achieve the high levels of accuracy demanded by most real applications. This is due to the fact that changes in pixel intensity are not a particularly good indicator of significant change in a scene. We propose a semantic change detection approach which aims to classify the content of an image before attempting to identify change. This technology builds upon recent developments in large-scale classification which have dramatically improved both accuracy and speed.

By identifying change in the contents of images, rather than the pixels, we aim to significantly improve the accuracy of image-based change detection.


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