S. Madan

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In modern visual clustering applications where datasets are large and updates with new data may be ongoing, methods of online clustering are extremely important. Online clustering algorithms incrementally cluster the data points, use a fraction of the dataset memory, and update the clustering decisions when new data comes in. In this paper we adapt a(More)
Conventional light striping systems capture 3D data by stereo reconstruction and employ encoding systems to solve the correspondence problem. A confounding factor in this overall framework is the interaction of light with surfaces. Light is absorbed by materials and current methods tend to perform poorly for dark objects. We present a new approach to(More)
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