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Building recognition from images is a challenging task since pictures can be taken from different angles and under different illumination conditions. Most of the building recognition methods use local and global handcrafted image features and do not consider the rejection scenario, where the method have to be capable of identifying if a given image does not belong to any of the classes of interest...
In this paper, we propose a post classification smoothing method aimed at improving the accuracy and visual appearance of sub-decimeter image classification results. Starting from the class confidence maps of a supervised classifier, we find a set of high confidence markers and propagate labels on an extended region adjacency graph. We apply the proposed method on a challenging 5cm resolution dataset...
The detection of copy–move image tampering is of paramount importance nowadays, mainly due to its potential use for misleading the opinion forming process of the general public. In this paper, we go beyond traditional forgery detectors and aim at combining different properties of copy–move detection approaches by modeling the problem on a multiscale behavior knowledge space, which encodes the output...
Very high resolution (VHR) images are large datasets for pixel annotation -- a process that has depended on the supervised training of an effective pixel classifier. Active learning techniques have mitigated this problem, but pixel descriptors are limited to local image information and the large number of pixels makes the response time to the user's actions impractical, during active learning. To...
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