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We study the problem of answering questions about images in the harder setting, where the test questions and corresponding images contain novel objects, which were not queried about in the training data. Such setting is inevitable in real world–owing to the heavy tailed distribution of the visual categories, there would be some objects which would not be annotated in the train set. We show...
Image forensics using sensor photo-response nonuniformity (PRNU) provides a powerful method for associating an image with the camera that captured the image. To preserve privacy despite the availability of this powerful tool, we present a new framework for image anonymization. We formulate anonymization as a feasibility problem subject to multiple constraints that seek to ensure non-detectability...
Among the panoply of applications enabled by the Internet of Things (IoT), smart and connected health care is a particularly important one. Networked sensors, either worn on the body or embedded in our living environments, make possible the gathering of rich information indicative of our physical and mental health. Captured on a continual basis, aggregated, and effectively mined, such information...
We propose an informed watermark embedding method in fractional Fourier domain. Detectability and imperceptibility of the watermark sequence constraints as well as real-valuedness in spatial domain are imposed on the resulting image using a set theoretic framework. Insertion of multiple bits without using a block based scheme is also a novel approach and provides improvement against synchronization...
Retrieving images for an arbitrary user query, provided in textual form, is a challenging problem. A recently proposed method addresses this by constructing a visual classifier with images returned by an internet image search engine, based on the user query, as positive images while using a fixed pool of negative images. However, in practice, not all the images obtained from internet image search...
In many visual classification tasks the spatial distribution of discriminative information is (i) non uniform e.g. person ‘reading’ can be distinguished from ‘taking a photo’ based on the area around the arms i.e. ignoring the legs and (ii) has intra class variations e.g. different readers may hold the books differently. Motivated by these observations, we propose to learn the discriminative spatial...
We present a method for embedding and detection of visual watermark patterns in printed images that use clustered-dot halftones in the printing process. The method allows two independent watermark patterns to be multiplexed, i.e. embedded in the same region of the printed image, thereby offering an improvement over prior techniques. The watermark patterns are embedded via phase modulation along the...
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