(Created page with " == Abstract == Traffic sign detection is crucial in intelligent vehi- cles, no matter if one's objective is to develop Advanced Driver Assistance Systems or autonomous cars....") |
m (Scipediacontent moved page Draft Content 252983677 to Mogelmose et al 2014a) |
(No difference)
|
Traffic sign detection is crucial in intelligent vehi- cles, no matter if one's objective is to develop Advanced Driver Assistance Systems or autonomous cars. Recent advances in traffic sign detection, especially the great effort put into the competition German Traffic Sign Detection Benchmark, have given rise to very reliable detection systems when tested on European signs. The U.S., however, has a rather different approach to traffic sign design. This paper evaluates whether a current state-of-the-art traffic sign detector is useful for American signs. We find that for colorful, distinctively shaped signs, Integral Channel Features work well, but it fails on the large superclass of speed limit signs and similar designs. We also introduce an extension to the largest public dataset of American signs, the LISA Traffic Sign Dataset, and present an evaluation of tracking in the context of sign detection. We show that tracking essentially suppresses all false positives in our test set, and argue that in order to be useful for higher level analysis, any traffic sign detection system should contain tracking.
The different versions of the original document can be found in:
Published on 01/01/2014
Volume 2014, 2014
DOI: 10.1109/itsc.2014.6957882
Licence: CC BY-NC-SA license
Are you one of the authors of this document?