|Description (include details on usage, files and paper references)||The automotive multi-sensor (AMUSE) dataset consists of inertial and other complementary sensor data combined with monocular, omnidirectional, high frame rate visual data taken in real traffic scenes during multiple test drives.
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A short description of the dataset can be found in the paper published:
Philipp Koschorrek and Tommaso Piccini and Per Öberg and
Michael Felsberg and Lars Nielsen and Rudolf Mester
A multi-sensor traffic scene dataset with omnidirectional video
Ground Truth - What is a good dataset? CVPR Workshop 2013