Informedia at TRECVID 2003: Analyzing and searching broadcast news video

We submitted a number of semantic classifiers, most of which were merely trained on keyframes. We also experimented with runs of classifiers were trained exclusively on text data and relative time within the video, while a few were trained using all available multiple modalities. 1.2 Interactive search This year, we submitted two runs using different versions of the Informedia systems. In one run, a version identical to last year's interactive system was used by five researchers, who split up the topics between themselves. The system interface emphasizes text queries, allowing search across ASR, closed captions and OCR text. The result set can then be manipulated through: • storyboards of images spanning across video story segments • emphasizing matching shots to a user’s query to reduce the image count to a manageable size • resolution and layout under user control • additional filtering provided through shot classifiers such as outdoors, and shots with people, etc. • display of filter count and distribution to guide their use in manipulating storyboard views. In the best-performing interactive run, for all topics a single researcher used an improved version of the system, which allowed more effective browsing and visualization of the results of text queries using

The State of the Art in Cartograms

Cartograms combine statistical and geographical information in thematic maps, where areas of geographical regions (e.g., countries, states) are scaled in proportion to some statistic (e.g., population, income). Cartograms make it possible to gain insight into patterns and trends in the world around us and have been very popular visualizations for geo-referenced data for over a century. This work surveys cartogram research in visualization, cartography and geometry, covering a broad spectrum of different cartogram types: from the traditional rectangular and table cartograms, to Dorling and diffusion cartograms. A particular focus is the study of the major cartogram dimensions: statistical accuracy, geographical accuracy, and topological accuracy. We review the history of cartograms, describe the algorithms for generating them, and consider task taxonomies. We also review quantitative and qualitative evaluations, and we use these to arrive at design guidelines and research challenges

Area and length preserving geometric invariant scale-spaces

Caption title.Includes bibliographical references (p. 23-27).Supported by the National Science Foundation. DMS-8811084 ECS-9122106 Supported by the Air Force Office of Scientific Research. AFOSR-90-0024 Supported by the Army Research Office. DAAL03-91-G-0019 DAAL03-92-G-0115 Supported by the Rothschild Foundation-Yad Hanadiv.Guillermo Sapiro, Allen Tannenbaum

Shapley Supercluster Survey (ShaSS): Galaxy Evolution from Filaments to Cluster Cores

We present an overview of a multi-wavelength survey of the Shapley supercluster (SSC; z~0.05) covering a contiguous area of 260 h^-2_70 Mpc^2 including the supercluster core. The project main aim is to quantify the influence of cluster-scale mass assembly on galaxy evolution in one of the most massive structures in the local Universe. The Shapley supercluster survey (ShaSS) includes nine Abell clusters (A3552, A3554, A3556, A3558, A3559, A3560, A3562, AS0724, AS0726) and two poor clusters (SC1327- 312, SC1329-313) showing evidence of cluster-cluster interactions. Optical (ugri) and near-infrared (K) imaging acquired with VST and VISTA allow us to study the galaxy population down to m*+6 at the supercluster redshift. A dedicated spectroscopic survey with AAOmega on the Anglo-Australian Telescope provides a magnitude-limited sample of supercluster members with 80% completeness at ~m*+3. We derive the galaxy density across the whole area, demonstrating that all structures within this area are embedded in a single network of clusters, groups and filaments. The stellar mass density in the core of the SSC is always higher than 9E09 M_sun Mpc^-3, which is ~40x the cosmic stellar mass density for galaxies in the local Universe. We find a new filamentary structure (~7 Mpc long in projection) connecting the SSC core to the cluster A3559, as well as previously unidentified density peaks. We perform a weak-lensing analysis of the central 1 sqdeg field of the survey obtaining for the central cluster A3558 a mass of M_500=7.63E14 M_sun, in agreement with X-ray based estimates.Comment: 22 pages, 11 figures. Accepted for publication on MNRA

The Delta Tree: An Object-Centered Approach to Image-Based Rendering

This paper introduces the delta tree, a data structure that represents an object using a set of reference images. It also describes an algorithm for generating arbitrary re-projections of an object by traversing its delta tree. Delta trees are an efficient representation in terms of both storage and rendering performance. Each node of a delta tree stores an image taken from a point on a sampling sphere that encloses the object. Each image is compressed by discarding pixels that can be reconstructed by warping its ancestor's images to the node's viewpoint. The partial image stored at each node is divided into blocks and represented in the frequency domain. The rendering process generates an image at an arbitrary viewpoint by traversing the delta tree from a root node to one or more of its leaves. A subdivision algorithm selects only the required blocks from the nodes along the path. For each block, only the frequency components necessary to reconstruct the final image at an appropriate sampling density are used. This frequency selection mechanism handles both antialiasing and level-of-detail within a single framework. A complex scene is initially rendered by compositing images generated by traversing the delta trees of its components. Once the reference views of a scene are rendered once in this manner, the entire scene can be reprojected to an arbitrary viewpoint by traversing its own delta tree. Our approach is limited to generating views of an object from outside the object's convex hull. In practice we work around this problem by subdividing objects to render views from within the convex hull