Siddarth Sampangi

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Guiding principles for selecting the best crowdsourcing methodology for a given information gathering task remain insufficient. This paper contributes additional experimental evidence and analysis to this problem. Our work focuses on a subset of crowdsourcing problems we term expert tasks—tasks that require specific domain knowledge. We experiment with(More)
Robust real time tracking of multiple targets is a requisite feature for many applications. Online boosting has become an effective approach for dealing with the variability in object appearance. This approach can adapt its classifier to changes in appearance at the cost of additional runtime computation. In this paper, we address the task of accelerating(More)
Robust real time tracking is a requirement for many emerging applications. Many of these applications must track objects even as their appearance changes. Training classifiers online has become an effective approach for dealing with variability in object appearance. Classifiers can learn and adapt to changes online at the cost of additional runtime(More)
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