http://smartech.gatech.edu/handle/1853/14329 Interactive and intelligent computing is an emerging discipline on the frontier of ways computation impacts the external world. Search the Channel search http://smartech.gatech.edu/simple-search http://smartech.gatech.edu/handle/1853/25828 Title: Art or Circus? Characterizing User-Created Video on YouTube <br/> <br/>Authors: Landry, Brian M.; Guzdial, Mark <br/> <br/>Abstract: Video and networking technologies have advanced such that posting and viewing video online is practical. Everyday people now post video online to communicate asynchronously with remote audiences. This paper explores the forms in which people communicate on the popular video sharing website YouTube. It also examines whether end-user video creators on YouTube use plot-based storytelling as a communication strategy. We analyzed popular content on YouTube and found the majority of that content showcases everyday people engaging in uncommon activities. Furthermore, a small minority of popular video actually tells a story. Based on our findings, we propose the compostion gap as a means of conceptualizing the disparity between video content on You- Tube and professional content. We then discuss opportunities for designing technologies to support communication through performance-based video as well as story-based video. Mon, 29 Oct 2007 22:58:59 GMT http://smartech.gatech.edu/handle/1853/25827 Title: Localization and 3D Reconstruction of Urban Scenes Using GPS <br/> <br/>Authors: Kim, Kihwan; Summet, Jay; Starner, Thad; Ashbrook, Daniel; Kapade, Mrunal; Essa, Irfan A. <br/> <br/>Abstract: Using off-the-shelf Global Positioning System (GPS) units, we reconstruct buildings in 3D by exploiting the reduction in signal to noise ratio (SNR) that occurs when the buildings obstruct the line-of-sight between the moving units and the orbiting satellites. We measure the size and height of skyscrapers as well as automatically constructing a density map representing the location of multiple buildings in an urban landscape. If deployed on a large scale, via a cellular service provider’s GPS-enabled mobile phones or GPS-tracked delivery vehicles, the system could provide an inexpensive means of continuously creating and updating 3D maps of urban environments. Mon, 29 Oct 2007 22:58:59 GMT http://smartech.gatech.edu/handle/1853/25823 Title: Automatic Landmark Detection for Topological Mapping Using Bayesian Surprise <br/> <br/>Authors: Ranganathan, Ananth; Dellaert, Frank <br/> <br/>Abstract: Topological maps are graphical representations of the environment consisting of nodes that denote landmarks, and edges that represent the connectivity between the landmarks. Automatic detection of landmarks, usually special places in the environment such as gateways, in a general, sensor-independent manner has proven to be a difficult task. We present a landmark detection scheme based on the notion of “surprise” that addresses these issues. The surprise associated with a measurement is defined as the change in the current model upon updating it using the measurement. We demonstrate that surprise is large when sudden changes in the environment occur, and hence, is a good indicator of landmarks. We evaluate our landmark detector using appearance and laser measurements both qualitatively and quantitatively. Part of this evaluation is performed in the context of a topological mapping algorithm, thus demonstrating the practical applicability of the detector. Mon, 29 Oct 2007 22:58:59 GMT http://smartech.gatech.edu/handle/1853/25821 Title: Compositional Classification <br/> <br/>Authors: Jones, Joshua <br/> <br/>Abstract: An intelligent system must routinely deal with massive information processing complexity. The research discussed in this document is concerned with finding representations and processes to deal with a part of this complexity. At a high level, the proposed idea is that a synthesis between the symbolic reasoning of classic artificial intelligence research and the statistical inference mechanisms of machine learning provides answers to some of these issues of complexity. This research is specifically concerned with a subset of classification problems that we call ”compositional classification”, where both the class label and values produced at internal nodes in the classification structure entail verifiable predictions. This research specifies and evaluates a technique for compositional classification. This investigation will consist of (i) implementing a framework for the construction of supervised classification learning systems that codifies the technique, (ii) instantiating a number of learning systems for various specific classification problems using the framework, (iii) using a synthetic problem setting to systematically vary the problem characteristics and system parameters and assess the impact on performance, and (iv) formally analyzing the properties of the technique. A central problem addressed by this technique is how diverse techniques for representation, reasoning and learning that arise from differing viewpoints on intelligence can be reconciled to form a consistent and effective whole. For example, how can neural network backpropagation and knowledge-based diagnosis be combined to achieve an effective structural credit assignment technique for a hybrid knowledge representation? Mon, 24 Mar 2008 22:58:59 GMT