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In-Depth Evaluation of Popular Interest Point Detectors on Video Streams

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Executive Summary

The authors present an in-depth evaluation of popular interest point detectors, which, in contrast to existing evaluations, is targeted towards the application in visual tracking and augmented reality. In particular, candidate algorithms, testbed, and performance criteria are chosen with respect to the application of visual tracking. They evaluate the impact of individual algorithm parameters and present results in terms of repeatability, number of features detected, and computation time. They also describe their method to semi-automatically generate ground truth in detail.

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