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CVPR
2010
IEEE

Unified Real-Time Tracking and Recognition with Rotation-Invariant Fast Features

13 years 10 months ago
Unified Real-Time Tracking and Recognition with Rotation-Invariant Fast Features
We present a method that unifies tracking and video content recognition with applications to Mobile Augmented Reality (MAR). We introduce the Radial Gradient Transform (RGT) and an approximate RGT, yielding the Rotation-Invariant, Fast Feature (RIFF) descriptor. We demonstrate that RIFF is fast enough for real-time tracking, while robust enough for large scale retrieval tasks. At 26× the speed, our trackingscheme obtains a more accurate global affine motionmodel than the Kanade Lucas Tomasi (KLT) tracker. The same descriptors can achieve 94% retrieval accuracy from a database of 104 images.
Gabriel Takacs, Vijay Chandrasekhar, Sam Tsai, Dav
Added 08 Apr 2010
Updated 14 May 2010
Type Conference
Year 2010
Where CVPR
Authors Gabriel Takacs, Vijay Chandrasekhar, Sam Tsai, David Chen, Radek Grzeszczuk, Bernd Girod
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