8,694 research outputs found
Semantic Retrieval and Automatic Annotation: Linear Transformations, Correlation and Semantic Spaces
No full textThis paper proposes a new technique for auto-annotation and semantic retrieval based upon the idea of linearly mapping an image feature space to a keyword space. The new technique is compared to several related techniques, and a number of salient points about each of the techniques are discussed and contrasted. The paper also discusses how these techniques might actually scale to a real-world retrieval problem, and demonstrates this though a case study of a semantic retrieval technique being used on a real-world data-set (with a mix of annotated and unannotated images) from a picture library
Semantic spaces revisited: investigating the performance of auto-annotation and semantic retrieval using semantic spaces
No full textSemantic spaces encode similarity relationships between objects as a function of position in a mathematical space. This paper discusses three different formulations for building semantic spaces which allow the automatic-annotation and semantic retrieval of images. The models discussed in this paper require that the image content be described in the form of a series of visual-terms, rather than as a continuous feature-vector. The paper also discusses how these term-based models compare to the latest state-of-the-art continuous feature models for auto-annotation and retrieval
Giving order to image queries
No full textUsers of image retrieval systems often find it frustrating that the image they are looking for is not ranked near the top of the results they are presented. This paper presents a computational approach for ranking keyworded images in order of relevance to a given keyword. Our approach uses machine learning to attempt to learn what visual features within an image are most related to the keywords, and then provide ranking based on similarity to a visual aggregate. To evaluate the technique, a Web 2.0 application has been developed to obtain a corpus of user-generated ranking information for a given image collection that can be used to evaluate the performance of the ranking algorithm
Dataset "Privacy-aware image classification and search"
No full textModern content sharing environments such as Flickr or YouTube contain a large number of private resources such as photos showing weddings, family holidays, and private parties. These resources can be of a highly sensitive nature, disclosing many details of the users' private sphere. In order to support users in making privacy decisions in the context of image sharing and to provide them with a better overview of privacy-related visual content available on the Web, we propose techniques to automatically detect private images and to enable privacy-oriented image search. In order to classify images, we use the metadata like title and tags and plan to use visual features which are described in our scientific paper. The data set used in the paper is now available. Picalet! cleaned dataset - ( recommended for experiments) userstudy - (images annotated with queries, anonymized user id and privacy value)</span
MapSnapper: Engineering an Efficient Algorithm for Matching Images of Maps from Mobile Phones
No full textThe MapSnapper project aimed to develop a system for robust matching of low-quality images of a paper map taken from a mobile phone against a high quality digital raster representation of the same map. The paper presents a novel methodology for performing content-based image retrieval and object recognition from query images that have been degraded by noise and subjected to transformations through the imaging system. In addition the paper also provides an insight into the evaluation-driven development process that was used to incrementally improve the matching performance until the design specifications were met
IAM@ImageCLEFPhotoAnnotation 2009: Naïve application of a linear-algebraic semantic space
No full textThis paper describes Southampton's submissions to the 2009 ImageCLEF photo annotation task. For the task we used an annotation system based on the idea of constructing semantic spaces, which was developed previously at Southampton. To represent the image content, we used a combination of different SIFT and Colour-SIFT features detected using the difference-of-Gaussian and MSER techniques. These features were converted into a visual term representation by applying vector quantisation using a codebook learnt from a hierarchical k-means clustering. In terms of EER and AUC, the annotator performs reasonably well, however, it struggles when evaluated using the hierarchical measure proposed for the task, due to the way the annotation confidences are thresholded
Instructional Science and Engineering Videos
No full textThese fun, intelligent, and engaging videos were created by scientist Jonathan Hare to be used in schools, workshops, and in home-study with accompanying information. On the site, visitors can make their way through 25 short films that explore the worlds of infrared photography, light beams, parabolic light collectors, generators, and seawater batteries. The videos are about five minutes long, and they feature hands-on demonstrations, witty commentary, and scientific asides that are informative and accessible. Visitors can also sign up to receive updates when new videos are released or watch them via YouTube
Jonathan Ned Katz Author Event: The Daring Life and Dangerous Times of Eve Adam
No full text“The Daring Life and Dangerous Times of Eve Adams,” interview with author, Jonathan Ned Katz, moderated by Emily Weiner (WWU) and organized by Congregation Beth Israel
Contemporary Literature. Analysis of Jonathan Bazzi's novels
No full textopenDopo una breve panoramica della letteratura italiana degli ultimi vent’anni si analizzano i due romanzi di Jonathan Bazzi "Febbre" e "Corpi minori" dai punti di vista formale, stilistico e tematico. Si discute inoltre il rapporto tra social media, autofiction e autore; nel capitolo 4 si riporta l'intervista che Bazzi ci ha gentilmente concesso, in cui questi argomenti vengono ripresi.
Si individuano alcune differenze che i testi mostrano rispetto alla letteratura moderna, e gli aspetti che hanno in comune con quella contemporanea; nel fare questo si accennano quindi alcune caratteristiche della società che li ha prodotti.The paper starts off with a brief overview of the contemporary Italian literature; then the reader is guided through an analysis of Jonathan Bazzi's novels, "Febbre" ("Fever") and "Corpi minori" ("Minor bodies"), both translated in English and published by Scribe. The relationship between author, autofiction and social media will also be discussed; in chapter four the reader will find the interview Bazzi kindly granted us
OpenIMAJ and ImageTerrier: Java Libraries and Tools for Scalable Multimedia Analysis and Indexing of Images
No full textOpenIMAJ and ImageTerrier are recently released open-source libraries and tools for experimentation and development of multimedia applications using Java-compatible programming languages. OpenIMAJ (the Open toolkit for Intelligent Multimedia Analysis in Java) is a collection of libraries for multimedia analysis. The image libraries contain methods for processing images and extracting state- of-the-art features, including SIFT. The video and audio libraries support both cross-platform capture and processing. The clustering and nearest-neighbour libraries contain efficient, multi-threaded implementations of clustering algorithms. The clustering library makes it possible to easily create BoVW representations for images and videos. OpenI-MAJ also incorporates a number of tools to enable extremely- large-scale multimedia analysis using distributed computing with Apache Hadoop. ImageTerrier is a scalable, high-performance search engine platform for content-based image retrieval applications using features extracted with the OpenIMAJ library and tools. The ImageTerrier platform provides a comprehensive test-bed for experimenting with image retrieval techniques. The platform incorporates a state-of-the-art implementation of the single-pass indexing technique for constructing inverted indexes and is capable of producing highly compressed index data structures
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