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We present a system that can reconstruct 3D geometry from large, unorganized collections of photographs such as those found by searching for a given city (e.g., Rome) on Internet photo-sharing sites. Our system is built on a set of new, distributed computer vision algorithms for image matching and 3D reconstruction, designed to maximize parallelism at each(More)
We formulate the problem of scene summarization as selecting a set of images that efficiently represents the visual content of a given scene. The ideal summary presents the most interesting and important aspects of the scene with minimal redundancy. We propose a solution to this problem using multi-user image collections from the Internet. Our solution(More)
Recent progress is described in digitizing and visualizing the world from data captured by people taking photos and uploading them to the web. ABSTRACT | There are billions of photographs on the Internet, representing an extremely large, rich, and nearly comprehensive visual record of virtually every famous place on Earth. Unfortunately , these massive(More)
As machine learning (ML) systems emerge in end-user applications, learning algorithms and classifiers will need to be robust to an increasingly unpredictable operating environment. In many cases, the parameters governing a learning system cannot be optimized for every user scenario, nor can users typically manipulate parameters defined in the space and(More)
Viruses have substantial value as vehicles for transporting transgenes into neurons. Each virus has its own set of attributes for addressing neuroscience-related questions. Here we review some of the advantages and limitations of herpes, pseudorabies, rabies, adeno-associated, lentivirus, and others to study the brain. We then explore a novel recombinant(More)
This paper describes a method for creating new music by concatenative synthesis. Given a MIDI score and an audio recording of an example piece of monophonic music, our method synthesizes audio to correspond with a new MIDI score. The algorithm we use is based on concate-native synthesis, commonly used for generating speech. Two versions of our algorithm are(More)
We describe a method for fully automatic object recognition and segmentation using a set of reference images to specify the appearance of each object. Our method uses a generative model of image formation that takes into account occlusions, simple lighting changes, and object deformations. We take advantage of local features to identify, locate, and extract(More)